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Sample records for adaptive system identification

  1. Identification of nonlinear optical systems using adaptive kernel methods

    NASA Astrophysics Data System (ADS)

    Wang, Xiaodong; Zhang, Changjiang; Zhang, Haoran; Feng, Genliang; Xu, Xiuling

    2005-12-01

    An identification approach of nonlinear optical dynamic systems, based on adaptive kernel methods which are modified version of least squares support vector machine (LS-SVM), is presented in order to obtain the reference dynamic model for solving real time applications such as adaptive signal processing of the optical systems. The feasibility of this approach is demonstrated with the computer simulation through identifying a Bragg acoustic-optical bistable system. Unlike artificial neural networks, the adaptive kernel methods possess prominent advantages: over fitting is unlikely to occur by employing structural risk minimization criterion, the global optimal solution can be uniquely obtained owing to that its training is performed through the solution of a set of linear equations. Also, the adaptive kernel methods are still effective for the nonlinear optical systems with a variation of the system parameter. This method is robust with respect to noise, and it constitutes another powerful tool for the identification of nonlinear optical systems.

  2. The reduced order model problem in distributed parameter systems adaptive identification and control. [adaptive control of flexible spacecraft

    NASA Technical Reports Server (NTRS)

    Johnson, C. R., Jr.; Lawrence, D. A.

    1981-01-01

    The reduced order model problem in distributed parameter systems adaptive identification and control is investigated. A comprehensive examination of real-time centralized adaptive control options for flexible spacecraft is provided.

  3. Adaptive identification and control of structural dynamics systems using recursive lattice filters

    NASA Technical Reports Server (NTRS)

    Sundararajan, N.; Montgomery, R. C.; Williams, J. P.

    1985-01-01

    A new approach for adaptive identification and control of structural dynamic systems by using least squares lattice filters thar are widely used in the signal processing area is presented. Testing procedures for interfacing the lattice filter identification methods and modal control method for stable closed loop adaptive control are presented. The methods are illustrated for a free-free beam and for a complex flexible grid, with the basic control objective being vibration suppression. The approach is validated by using both simulations and experimental facilities available at the Langley Research Center.

  4. Development of an adaptive failure detection and identification system for detecting aircraft control element failures

    NASA Technical Reports Server (NTRS)

    Bundick, W. Thomas

    1990-01-01

    A methodology for designing a failure detection and identification (FDI) system to detect and isolate control element failures in aircraft control systems is reviewed. An FDI system design for a modified B-737 aircraft resulting from this methodology is also reviewed, and the results of evaluating this system via simulation are presented. The FDI system performed well in a no-turbulence environment, but it experienced an unacceptable number of false alarms in atmospheric turbulence. An adaptive FDI system, which adjusts thresholds and other system parameters based on the estimated turbulence level, was developed and evaluated. The adaptive system performed well over all turbulence levels simulated, reliably detecting all but the smallest magnitude partially-missing-surface failures.

  5. Performance study of LMS based adaptive algorithms for unknown system identification

    SciTech Connect

    Javed, Shazia; Ahmad, Noor Atinah

    2014-07-10

    Adaptive filtering techniques have gained much popularity in the modeling of unknown system identification problem. These techniques can be classified as either iterative or direct. Iterative techniques include stochastic descent method and its improved versions in affine space. In this paper we present a comparative study of the least mean square (LMS) algorithm and some improved versions of LMS, more precisely the normalized LMS (NLMS), LMS-Newton, transform domain LMS (TDLMS) and affine projection algorithm (APA). The performance evaluation of these algorithms is carried out using adaptive system identification (ASI) model with random input signals, in which the unknown (measured) signal is assumed to be contaminated by output noise. Simulation results are recorded to compare the performance in terms of convergence speed, robustness, misalignment, and their sensitivity to the spectral properties of input signals. Main objective of this comparative study is to observe the effects of fast convergence rate of improved versions of LMS algorithms on their robustness and misalignment.

  6. Performance study of LMS based adaptive algorithms for unknown system identification

    NASA Astrophysics Data System (ADS)

    Javed, Shazia; Ahmad, Noor Atinah

    2014-07-01

    Adaptive filtering techniques have gained much popularity in the modeling of unknown system identification problem. These techniques can be classified as either iterative or direct. Iterative techniques include stochastic descent method and its improved versions in affine space. In this paper we present a comparative study of the least mean square (LMS) algorithm and some improved versions of LMS, more precisely the normalized LMS (NLMS), LMS-Newton, transform domain LMS (TDLMS) and affine projection algorithm (APA). The performance evaluation of these algorithms is carried out using adaptive system identification (ASI) model with random input signals, in which the unknown (measured) signal is assumed to be contaminated by output noise. Simulation results are recorded to compare the performance in terms of convergence speed, robustness, misalignment, and their sensitivity to the spectral properties of input signals. Main objective of this comparative study is to observe the effects of fast convergence rate of improved versions of LMS algorithms on their robustness and misalignment.

  7. Adaptive modeling, identification, and control of dynamic structural systems. I. Theory

    USGS Publications Warehouse

    Safak, Erdal

    1989-01-01

    A concise review of the theory of adaptive modeling, identification, and control of dynamic structural systems based on discrete-time recordings is presented. Adaptive methods have four major advantages over the classical methods: (1) Removal of the noise from the signal is done over the whole frequency band; (2) time-varying characteristics of systems can be tracked; (3) systems with unknown characteristics can be controlled; and (4) a small segment of the data is needed during the computations. Included in the paper are the discrete-time representation of single-input single-output (SISO) systems, models for SISO systems with noise, the concept of stochastic approximation, recursive prediction error method (RPEM) for system identification, and the adaptive control. Guidelines for model selection and model validation and the computational aspects of the method are also discussed in the paper. The present paper is the first of two companion papers. The theory given in the paper is limited to that which is necessary to follow the examples for applications in structural dynamics presented in the second paper.

  8. Lithofacies identification using multiple adaptive resonance theory neural networks and group decision expert system

    USGS Publications Warehouse

    Chang, H.-C.; Kopaska-Merkel, D. C.; Chen, H.-C.; Rocky, Durrans S.

    2000-01-01

    Lithofacies identification supplies qualitative information about rocks. Lithofacies represent rock textures and are important components of hydrocarbon reservoir description. Traditional techniques of lithofacies identification from core data are costly and different geologists may provide different interpretations. In this paper, we present a low-cost intelligent system consisting of three adaptive resonance theory neural networks and a rule-based expert system to consistently and objectively identify lithofacies from well-log data. The input data are altered into different forms representing different perspectives of observation of lithofacies. Each form of input is processed by a different adaptive resonance theory neural network. Among these three adaptive resonance theory neural networks, one neural network processes the raw continuous data, another processes categorial data, and the third processes fuzzy-set data. Outputs from these three networks are then combined by the expert system using fuzzy inference to determine to which facies the input data should be assigned. Rules are prioritized to emphasize the importance of firing order. This new approach combines the learning ability of neural networks, the adaptability of fuzzy logic, and the expertise of geologists to infer facies of the rocks. This approach is applied to the Appleton Field, an oil field located in Escambia County, Alabama. The hybrid intelligence system predicts lithofacies identity from log data with 87.6% accuracy. This prediction is more accurate than those of single adaptive resonance theory networks, 79.3%, 68.0% and 66.0%, using raw, fuzzy-set, and categorical data, respectively, and by an error-backpropagation neural network, 57.3%. (C) 2000 Published by Elsevier Science Ltd. All rights reserved.

  9. Low power proton exchange membrane fuel cell system identification and adaptive control

    NASA Astrophysics Data System (ADS)

    Yang, Yee-Pien; Wang, Fu-Cheng; Chang, Hsin-Ping; Ma, Ying-Wei; Weng, Biing-Jyh

    This paper proposes a systematic method of system identification and control of a proton exchange membrane (PEM) fuel cell. This fuel cell can be used for low-power communication devices involving complex electrochemical reactions of nonlinear and time-varying dynamic properties. From a system point of view, the dynamic model of PEM fuel cell is reduced to a configuration of two inputs, hydrogen and air flow rates, and two outputs, cell voltage and current. The corresponding transfer functions describe linearized subsystem dynamics with finite orders and time-varying parameters, which are expressed as discrete-time auto-regression moving-average with auxiliary input models for system identification by the recursive least square algorithm. In the experiments, a pseudo-random binary sequence of hydrogen or air flow rate is fed to a single fuel cell device to excite its dynamics. By measuring the corresponding output signals, each subsystem transfer function of reduced order is identified, while the unmodeled, higher-order dynamics and disturbances are described by the auxiliary input term. This provides a basis of adaptive control strategy to improve the fuel cell performance in terms of efficiency, as well as transient and steady state specifications. Simulation shows that adaptive controller is robust to the variation of fuel cell system dynamics, and it has proved promising from the experimental results.

  10. Systems identification and the adaptive management of waterfowl in the United States

    USGS Publications Warehouse

    Williams, B.K.; Nichols, J.D.

    2001-01-01

    Waterfowl management in the United States is one of the more visible conservation success stories in the United States. It is authorized and supported by appropriate legislative authorities, based on large-scale monitoring programs, and widely accepted by the public. The process is one of only a limited number of large-scale examples of effective collaboration between research and management, integrating scientific information with management in a coherent framework for regulatory decision-making. However, harvest management continues to face some serious technical problems, many of which focus on sequential identification of the resource system in a context of optimal decision-making. The objective of this paper is to provide a theoretical foundation of adaptive harvest management, the approach currently in use in the United States for regulatory decision-making. We lay out the legal and institutional framework for adaptive harvest management and provide a formal description of regulatory decision-making in terms of adaptive optimization. We discuss some technical and institutional challenges in applying adaptive harvest management and focus specifically on methods of estimating resource states for linear resource systems.

  11. Identification and adaptive neural network control of a DC motor system with dead-zone characteristics.

    PubMed

    Peng, Jinzhu; Dubay, Rickey

    2011-10-01

    In this paper, an adaptive control approach based on the neural networks is presented to control a DC motor system with dead-zone characteristics (DZC), where two neural networks are proposed to formulate the traditional identification and control approaches. First, a Wiener-type neural network (WNN) is proposed to identify the motor DZC, which formulates the Wiener model with a linear dynamic block in cascade with a nonlinear static gain. Second, a feedforward neural network is proposed to formulate the traditional PID controller, termed as PID-type neural network (PIDNN), which is then used to control and compensate for the DZC. In this way, the DC motor system with DZC is identified by the WNN identifier, which provides model information to the PIDNN controller in order to make it adaptive. Back-propagation algorithms are used to train both neural networks. Also, stability and convergence analysis are conducted using the Lyapunov theorem. Finally, experiments on the DC motor system demonstrated accurate identification and good compensation for dead-zone with improved control performance over the conventional PID control.

  12. An on-line equivalent system identification scheme for adaptive control. Ph.D. Thesis - Stanford Univ.

    NASA Technical Reports Server (NTRS)

    Sliwa, S. M.

    1984-01-01

    A prime obstacle to the widespread use of adaptive control is the degradation of performance and possible instability resulting from the presence of unmodeled dynamics. The approach taken is to explicitly include the unstructured model uncertainty in the output error identification algorithm. The order of the compensator is successively increased by including identified modes. During this model building stage, heuristic rules are used to test for convergence prior to designing compensators. Additionally, the recursive identification algorithm as extended to multi-input, multi-output systems. Enhancements were also made to reduce the computational burden of an algorithm for obtaining minimal state space realizations from the inexact, multivariate transfer functions which result from the identification process. A number of potential adaptive control applications for this approach are illustrated using computer simulations. Results indicated that when speed of adaptation and plant stability are not critical, the proposed schemes converge to enhance system performance.

  13. Aircraft Abnormal Conditions Detection, Identification, and Evaluation Using Innate and Adaptive Immune Systems Interaction

    NASA Astrophysics Data System (ADS)

    Al Azzawi, Dia

    Abnormal flight conditions play a major role in aircraft accidents frequently causing loss of control. To ensure aircraft operation safety in all situations, intelligent system monitoring and adaptation must rely on accurately detecting the presence of abnormal conditions as soon as they take place, identifying their root cause(s), estimating their nature and severity, and predicting their impact on the flight envelope. Due to the complexity and multidimensionality of the aircraft system under abnormal conditions, these requirements are extremely difficult to satisfy using existing analytical and/or statistical approaches. Moreover, current methodologies have addressed only isolated classes of abnormal conditions and a reduced number of aircraft dynamic parameters within a limited region of the flight envelope. This research effort aims at developing an integrated and comprehensive framework for the aircraft abnormal conditions detection, identification, and evaluation based on the artificial immune systems paradigm, which has the capability to address the complexity and multidimensionality issues related to aircraft systems. Within the proposed framework, a novel algorithm was developed for the abnormal conditions detection problem and extended to the abnormal conditions identification and evaluation. The algorithm and its extensions were inspired from the functionality of the biological dendritic cells (an important part of the innate immune system) and their interaction with the different components of the adaptive immune system. Immunity-based methodologies for re-assessing the flight envelope at post-failure and predicting the impact of the abnormal conditions on the performance and handling qualities are also proposed and investigated in this study. The generality of the approach makes it applicable to any system. Data for artificial immune system development were collected from flight tests of a supersonic research aircraft within a motion-based flight

  14. The reduced order model problem in distributed parameter systems adaptive identification and control

    NASA Technical Reports Server (NTRS)

    Johnson, C. R., Jr.

    1980-01-01

    The research concerning the reduced order model problem in distributed parameter systems is reported. The adaptive control strategy was chosen for investigation in the annular momentum control device. It is noted, that if there is no observation spill over, and no model errors, an indirect adaptive control strategy can be globally stable. Recent publications concerning adaptive control are included.

  15. Implementation for temporal noise identification using adaptive threshold of infrared imaging system

    NASA Astrophysics Data System (ADS)

    Lim, Inok

    2007-10-01

    Bad pixels are spatial or temporal noise which arise from dead pixels by fixed signal levels or blinking pixels by variable signal levels that go beyond the bounds of normal pixel levels at the temperature. Because bad pixels are the false targets over infrared imaging system for tracking, those must be corrected. Main contribution to the number of bad pixels is fixed pattern noise (FPN) according to increasing array size. And it is more simple to establish whether FPN is or not through analyzing of accumulated frames. But it needs to calculate with more complex implementation such standard deviation from frame to frame in case of the temporal noise. Both cases it is very important to establish the threshold levels for identifying at variable operating temperatures. In this paper, we propose a more efficient data analysis method and a temporal noise identification method using adaptive threshold for infrared imaging system, and the hardware is implemented to identify and replace bad pixels. And its result is confirmed visually by bad pixel map images.

  16. Assessment of Multi-Joint Coordination and Adaptation in Standing Balance: A Novel Device and System Identification Technique.

    PubMed

    Engelhart, Denise; Schouten, Alfred C; Aarts, Ronald G K M; van der Kooij, Herman

    2015-11-01

    The ankles and hips play an important role in maintaining standing balance and the coordination between joints adapts with task and conditions, like the disturbance magnitude and type, and changes with age. Assessment of multi-joint coordination requires the application of multiple continuous and independent disturbances and closed loop system identification techniques (CLSIT). This paper presents a novel device, the double inverted pendulum perturbator (DIPP), which can apply disturbing forces at the hip level and between the shoulder blades. In addition to the disturbances, the device can provide force fields to study adaptation of multi-joint coordination. The performance of the DIPP and a novel CLSIT was assessed by identifying a system with known mechanical properties and model simulations. A double inverted pendulum was successfully identified, while force fields were able to keep the pendulum upright. The estimated dynamics were similar as the theoretical derived dynamics. The DIPP has a sufficient bandwidth of 7 Hz to identify multi-joint coordination dynamics. An experiment with human subjects where a stabilizing force field was rendered at the hip (1500 N/m), showed that subjects adapt by lowering their control actions around the ankles. The stiffness from upper and lower segment motion to ankle torque dropped with 30% and 48%, respectively. Our methods allow to study (pathological) changes in multi-joint coordination as well as adaptive capacity to maintain standing balance. PMID:25423654

  17. Assessment of Multi-Joint Coordination and Adaptation in Standing Balance: A Novel Device and System Identification Technique.

    PubMed

    Engelhart, Denise; Schouten, Alfred C; Aarts, Ronald G K M; van der Kooij, Herman

    2015-11-01

    The ankles and hips play an important role in maintaining standing balance and the coordination between joints adapts with task and conditions, like the disturbance magnitude and type, and changes with age. Assessment of multi-joint coordination requires the application of multiple continuous and independent disturbances and closed loop system identification techniques (CLSIT). This paper presents a novel device, the double inverted pendulum perturbator (DIPP), which can apply disturbing forces at the hip level and between the shoulder blades. In addition to the disturbances, the device can provide force fields to study adaptation of multi-joint coordination. The performance of the DIPP and a novel CLSIT was assessed by identifying a system with known mechanical properties and model simulations. A double inverted pendulum was successfully identified, while force fields were able to keep the pendulum upright. The estimated dynamics were similar as the theoretical derived dynamics. The DIPP has a sufficient bandwidth of 7 Hz to identify multi-joint coordination dynamics. An experiment with human subjects where a stabilizing force field was rendered at the hip (1500 N/m), showed that subjects adapt by lowering their control actions around the ankles. The stiffness from upper and lower segment motion to ankle torque dropped with 30% and 48%, respectively. Our methods allow to study (pathological) changes in multi-joint coordination as well as adaptive capacity to maintain standing balance.

  18. The reduced order model problem in distributed parameter systems adaptive identification and control. [large space structures

    NASA Technical Reports Server (NTRS)

    Johnson, C. R., Jr.; Lawrence, D.

    1981-01-01

    The basic assumption that a large space structure can be decoupled preceding the application of reduced order active control was considered and alternative solutions to the control of such structures (in contrast to the strict modal control) were investigated. The transfer function matrix from the actuators to the sensors was deemed to be a reasonable candidate. More refined models from multivariable systems theory were studied and recent results in the multivariable control field were compared with respect to theoretical deficiencies and likely problems in application to large space structures.

  19. Dynamic modeling of breast tissue with application of model reference adaptive system identification technique based on clinical robot-assisted palpation.

    PubMed

    Keshavarz, M; Mojra, A

    2015-11-01

    Accurate identification of breast tissue's dynamic behavior in physical examination is critical to successful diagnosis and treatment. In this study a model reference adaptive system identification (MRAS) algorithm is utilized to estimate the dynamic behavior of breast tissue from mechanical stress-strain datasets. A robot-assisted device (Robo-Tac-BMI) is going to mimic physical palpation on a 45 year old woman having a benign mass in the left breast. Stress-strain datasets will be collected over 14 regions of both breasts in a specific period of time. Then, a 2nd order linear model is adapted to the experimental datasets. It was confirmed that a unique dynamic model with maximum error about 0.89% is descriptive of the breast tissue behavior meanwhile mass detection may be achieved by 56.1% difference from the normal tissue.

  20. A novel online adaptive time delay identification technique

    NASA Astrophysics Data System (ADS)

    Bayrak, Alper; Tatlicioglu, Enver

    2016-05-01

    Time delay is a phenomenon which is common in signal processing, communication, control applications, etc. The special feature of time delay that makes it attractive is that it is a commonly faced problem in many systems. A literature search on time-delay identification highlights the fact that most studies focused on numerical solutions. In this study, a novel online adaptive time-delay identification technique is proposed. This technique is based on an adaptive update law through a minimum-maximum strategy which is firstly applied to time-delay identification. In the design of the adaptive identification law, Lyapunov-based stability analysis techniques are utilised. Several numerical simulations were conducted with Matlab/Simulink to evaluate the performance of the proposed technique. It is numerically demonstrated that the proposed technique works efficiently in identifying both constant and disturbed time delays, and is also robust to measurement noise.

  1. Adaptive spectroscopy for rapid chemical identification

    NASA Astrophysics Data System (ADS)

    Dinakarababu, Dineshbabu V.; Gehm, Michael E.

    2009-05-01

    Spectroscopic chemical identification is fundamentally a classification task where sensor measurements are compared to a library of known compounds with the hope of determining an unambiguous match. When the measurement signal-to-noise ratio (SNR) is very low (e.g. from short exposure times, weak analyte signatures, etc.), classification can become very challenging, requiring a multiple-measurement framework such as sequential hypothesis testing, and dramatically extending the time required to classify the sample. There are a wide variety of defense, security, and medical applications where rapid identification is essential, and hence such delays are disastrous. In this paper, we discuss an approach for adaptive spectroscopic detection where the introduction of a tunable spectral filter enables the system to measure the projection of the sample spectrum along arbitrary bases in the spectral domain. The net effect is a significant reduction in time-to-decision in low SNR cases. We describe the general operation of such an instrument, present results from initial simulations, and report on our experimental progress.

  2. Adaptive Modal Identification for Flutter Suppression Control

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.; Drew, Michael; Swei, Sean S.

    2016-01-01

    In this paper, we will develop an adaptive modal identification method for identifying the frequencies and damping of a flutter mode based on model-reference adaptive control (MRAC) and least-squares methods. The least-squares parameter estimation will achieve parameter convergence in the presence of persistent excitation whereas the MRAC parameter estimation does not guarantee parameter convergence. Two adaptive flutter suppression control approaches are developed: one based on MRAC and the other based on the least-squares method. The MRAC flutter suppression control is designed as an integral part of the parameter estimation where the feedback signal is used to estimate the modal information. On the other hand, the separation principle of control and estimation is applied to the least-squares method. The least-squares modal identification is used to perform parameter estimation.

  3. Identification of propulsion systems

    NASA Technical Reports Server (NTRS)

    Merrill, Walter; Guo, Ten-Huei; Duyar, Ahmet

    1991-01-01

    This paper presents a tutorial on the use of model identification techniques for the identification of propulsion system models. These models are important for control design, simulation, parameter estimation, and fault detection. Propulsion system identification is defined in the context of the classical description of identification as a four step process that is unique because of special considerations of data and error sources. Propulsion system models are described along with the dependence of system operation on the environment. Propulsion system simulation approaches are discussed as well as approaches to propulsion system identification with examples for both air breathing and rocket systems.

  4. Verification of Adaptive Systems

    SciTech Connect

    Pullum, Laura L; Cui, Xiaohui; Vassev, Emil; Hinchey, Mike; Rouff, Christopher; Buskens, Richard

    2012-01-01

    Adaptive systems are critical for future space and other unmanned and intelligent systems. Verification of these systems is also critical for their use in systems with potential harm to human life or with large financial investments. Due to their nondeterministic nature and extremely large state space, current methods for verification of software systems are not adequate to provide a high level of assurance for them. The combination of stabilization science, high performance computing simulations, compositional verification and traditional verification techniques, plus operational monitors, provides a complete approach to verification and deployment of adaptive systems that has not been used before. This paper gives an overview of this approach.

  5. Adaptive Identification and Control of Flow-Induced Cavity Oscillations

    NASA Technical Reports Server (NTRS)

    Kegerise, M. A.; Cattafesta, L. N.; Ha, C.

    2002-01-01

    Progress towards an adaptive self-tuning regulator (STR) for the cavity tone problem is discussed in this paper. Adaptive system identification algorithms were applied to an experimental cavity-flow tested as a prerequisite to control. In addition, a simple digital controller and a piezoelectric bimorph actuator were used to demonstrate multiple tone suppression. The control tests at Mach numbers of 0.275, 0.40, and 0.60 indicated approx. = 7dB tone reductions at multiple frequencies. Several different adaptive system identification algorithms were applied at a single freestream Mach number of 0.275. Adaptive finite-impulse response (FIR) filters of orders up to N = 100 were found to be unsuitable for modeling the cavity flow dynamics. Adaptive infinite-impulse response (IIR) filters of comparable order better captured the system dynamics. Two recursive algorithms, the least-mean square (LMS) and the recursive-least square (RLS), were utilized to update the adaptive filter coefficients. Given the sample-time requirements imposed by the cavity flow dynamics, the computational simplicity of the least mean squares (LMS) algorithm is advantageous for real-time control.

  6. Author Identification Systems

    ERIC Educational Resources Information Center

    Wagner, A. Ben

    2009-01-01

    Many efforts are currently underway to disambiguate author names and assign unique identification numbers so that publications by a given scholar can be reliably grouped together. This paper reviews a number of operational and in-development services. Some systems like ResearcherId.Com depend on self-registration and self-identification of a…

  7. Quantum system identification.

    PubMed

    Burgarth, Daniel; Yuasa, Kazuya

    2012-02-24

    The aim of quantum system identification is to estimate the ingredients inside a black box, in which some quantum-mechanical unitary process takes place, by just looking at its input-output behavior. Here we establish a basic and general framework for quantum system identification, that allows us to classify how much knowledge about the quantum system is attainable, in principle, from a given experimental setup. We show that controllable closed quantum systems can be estimated up to unitary conjugation. Prior knowledge on some elements of the black box helps the system identification. We present an example in which a Bell measurement is more efficient to identify the system. When the topology of the system is known, the framework enables us to establish a general criterion for the estimability of the coupling constants in its Hamiltonian.

  8. Model reference adaptive control, estimation and identification using only input and output signals

    NASA Technical Reports Server (NTRS)

    Carroll, R. L.; Monopoli, R. V.

    1975-01-01

    Significant recent advances in the application of stability theory to the adaptive control and identification of systems, and adaptive state estimation, are considered. Emphasis is on those methods which utilize only input and output measurements of the system, and do not require derivatives of the output signal.

  9. Optimized System Identification

    NASA Technical Reports Server (NTRS)

    Juang, Jer-Nan; Longman, Richard W.

    1999-01-01

    In system identification, one usually cares most about finding a model whose outputs are as close as possible to the true system outputs when the same input is applied to both. However, most system identification algorithms do not minimize this output error. Often they minimize model equation error instead, as in typical least-squares fits using a finite-difference model, and it is seen here that this distinction is significant. Here, we develop a set of system identification algorithms that minimize output error for multi-input/multi-output and multi-input/single-output systems. This is done with sequential quadratic programming iterations on the nonlinear least-squares problems, with an eigendecomposition to handle indefinite second partials. This optimization minimizes a nonlinear function of many variables, and hence can converge to local minima. To handle this problem, we start the iterations from the OKID (Observer/Kalman Identification) algorithm result. Not only has OKID proved very effective in practice, it minimizes an output error of an observer which has the property that as the data set gets large, it converges to minimizing the criterion of interest here. Hence, it is a particularly good starting point for the nonlinear iterations here. Examples show that the methods developed here eliminate the bias that is often observed using any system identification methods of either over-estimating or under-estimating the damping of vibration modes in lightly damped structures.

  10. An adaptive identification and control scheme for large space structures

    NASA Technical Reports Server (NTRS)

    Carroll, J. V.

    1988-01-01

    A unified identification and control scheme capable of achieving space at form performance objectives under nominal or failure conditions is described. Preliminary results are also presented, showing that the methodology offers much promise for effective robust control of large space structures. The control method is a multivariable, adaptive, output predictive controller called Model Predictive Control (MPC). MPC uses a state space model and input reference trajectories of set or tracking points to adaptively generate optimum commands. For a fixed model, MPC processes commands with great efficiency, and is also highly robust. A key feature of MPC is its ability to control either nonminimum phase or open loop unstable systems. As an output controller, MPC does not explicitly require full state feedback, as do most multivariable (e.g., Linear Quadratic) methods. Its features are very useful in LSS operations, as they allow non-collocated actuators and sensors. The identification scheme is based on canonical variate analysis (CVA) of input and output data. The CVA technique is particularly suited for the measurement and identification of structural dynamic processes - that is, unsteady transient or dynamically interacting processes such as between aerodynamics and structural deformation - from short, noisy data. CVA is structured so that the identification can be done in real or near real time, using computationally stable algorithms. Modeling LSS dynamics in 1-g laboratories has always been a major impediment not only to understanding their behavior in orbit, but also to controlling it. In cases where the theoretical model is not confirmed, current methods provide few clues concerning additional dynamical relationships that are not included in the theoretical models. CVA needs no a priori model data, or structure; all statistically significant dynamical states are determined using natural, entropy-based methods. Heretofore, a major limitation in applying adaptive

  11. Adaptive Neuro-fuzzy approach in friction identification

    NASA Astrophysics Data System (ADS)

    Zaiyad Muda @ Ismail, Muhammad

    2016-05-01

    Friction is known to affect the performance of motion control system, especially in terms of its accuracy. Therefore, a number of techniques or methods have been explored and implemented to alleviate the effects of friction. In this project, the Artificial Intelligent (AI) approach is used to model the friction which will be then used to compensate the friction. The Adaptive Neuro-Fuzzy Inference System (ANFIS) is chosen among several other AI methods because of its reliability and capabilities of solving complex computation. ANFIS is a hybrid AI-paradigm that combines the best features of neural network and fuzzy logic. This AI method (ANFIS) is effective for nonlinear system identification and compensation and thus, being used in this project.

  12. Identification and Control of Mechanical Systems

    NASA Astrophysics Data System (ADS)

    Juang, Jer-Nan; Phan, Minh Q.

    2001-08-01

    The control of vibrating systems is a significant issue in the design of aircraft, spacecraft, bridges, and high-rise buildings. This book discusses the control of vibrating systems, integrating structural dynamics, vibration analysis, modern control, and system identification. By integrating these subjects engineers will need only one book, rather than several texts or courses, to solve vibration control problems. The authors cover key developments in aerospace control and identification theory, including virtual passive control, observer and state-space identification, and data-based controller synthesis. They address many practical issues and applications, and show examples of how various methods are applied to real systems. Some methods show the close integration of system identification and control theory from the state-space perspective, rather than from the traditional input-output model perspective of adaptive control. This text will be useful for advanced undergraduate and beginning graduate students in aerospace, mechanical, and civil engineering, as well as for practicing engineers.

  13. Natural frequency identification of smart washer by using adaptive observer

    NASA Astrophysics Data System (ADS)

    Ito, Hitoshi; Okugawa, Masayuki

    2014-04-01

    Bolted joints are used in many machines/structures and some of them have been loosened during long time use, and unluckily these bolt loosening may cause a great accident of machines/structures system. These bolted joint, especially in important places, are main object of maintenance inspection. Maintenance inspection with human- involvement is desired to be improved owing to time-consuming, labor-intensive and high-cost. By remote and full automation monitoring of the bolt loosening, constantly monitoring of bolted joint is achieved. In order to detect loosening of bolted joints without human-involvement, applying a structural health monitoring technique and smart structures/materials concept is the key objective. In this study, a new method of bolt loosening detection by adopting a smart washer has been proposed, and the basic detection principle was discussed with numerical analysis about frequency equation of the system, was confirmed experimentally. The smart washer used in this study is in cantilever type with piezoelectric material, which adds the washer the self-sensing and actuation function. The principle used to detect the loosening of the bolts is a method of a bolt loosening detection noted that the natural frequency of a smart washer system is decreasing by the change of the bolt tightening axial tension. The feature of this proposed method is achieving to identify the natural frequency at current condition on demand by adopting the self-sensing and actuation function and system identification algorithm for varying the natural frequency depending the bolt tightening axial tension. A novel bolt loosening detection method by adopting adaptive observer is proposed in this paper. The numerical simulations are performed to verify the possibility of the adaptive observer-based loosening detection. Improvement of the detection accuracy for a bolt loosening is confirmed by adopting initial parameter and variable adaptive gain by numerical simulation.

  14. Adaptive protection algorithm and system

    DOEpatents

    Hedrick, Paul [Pittsburgh, PA; Toms, Helen L [Irwin, PA; Miller, Roger M [Mars, PA

    2009-04-28

    An adaptive protection algorithm and system for protecting electrical distribution systems traces the flow of power through a distribution system, assigns a value (or rank) to each circuit breaker in the system and then determines the appropriate trip set points based on the assigned rank.

  15. Adaptive ophthalmologic system

    DOEpatents

    Olivier, Scot S.; Thompson, Charles A.; Bauman, Brian J.; Jones, Steve M.; Gavel, Don T.; Awwal, Abdul A.; Eisenbies, Stephen K.; Haney, Steven J.

    2007-03-27

    A system for improving vision that can diagnose monochromatic aberrations within a subject's eyes, apply the wavefront correction, and then enable the patient to view the results of the correction. The system utilizes a laser for producing a beam of light; a corrector; a wavefront sensor; a testing unit; an optic device for directing the beam of light to the corrector, to the retina, from the retina to the wavefront sensor, and to the testing unit; and a computer operatively connected to the wavefront sensor and the corrector.

  16. Adaptive stimulus optimization for sensory systems neuroscience.

    PubMed

    DiMattina, Christopher; Zhang, Kechen

    2013-01-01

    In this paper, we review several lines of recent work aimed at developing practical methods for adaptive on-line stimulus generation for sensory neurophysiology. We consider various experimental paradigms where on-line stimulus optimization is utilized, including the classical optimal stimulus paradigm where the goal of experiments is to identify a stimulus which maximizes neural responses, the iso-response paradigm which finds sets of stimuli giving rise to constant responses, and the system identification paradigm where the experimental goal is to estimate and possibly compare sensory processing models. We discuss various theoretical and practical aspects of adaptive firing rate optimization, including optimization with stimulus space constraints, firing rate adaptation, and possible network constraints on the optimal stimulus. We consider the problem of system identification, and show how accurate estimation of non-linear models can be highly dependent on the stimulus set used to probe the network. We suggest that optimizing stimuli for accurate model estimation may make it possible to successfully identify non-linear models which are otherwise intractable, and summarize several recent studies of this type. Finally, we present a two-stage stimulus design procedure which combines the dual goals of model estimation and model comparison and may be especially useful for system identification experiments where the appropriate model is unknown beforehand. We propose that fast, on-line stimulus optimization enabled by increasing computer power can make it practical to move sensory neuroscience away from a descriptive paradigm and toward a new paradigm of real-time model estimation and comparison.

  17. Adaptive stimulus optimization for sensory systems neuroscience

    PubMed Central

    DiMattina, Christopher; Zhang, Kechen

    2013-01-01

    In this paper, we review several lines of recent work aimed at developing practical methods for adaptive on-line stimulus generation for sensory neurophysiology. We consider various experimental paradigms where on-line stimulus optimization is utilized, including the classical optimal stimulus paradigm where the goal of experiments is to identify a stimulus which maximizes neural responses, the iso-response paradigm which finds sets of stimuli giving rise to constant responses, and the system identification paradigm where the experimental goal is to estimate and possibly compare sensory processing models. We discuss various theoretical and practical aspects of adaptive firing rate optimization, including optimization with stimulus space constraints, firing rate adaptation, and possible network constraints on the optimal stimulus. We consider the problem of system identification, and show how accurate estimation of non-linear models can be highly dependent on the stimulus set used to probe the network. We suggest that optimizing stimuli for accurate model estimation may make it possible to successfully identify non-linear models which are otherwise intractable, and summarize several recent studies of this type. Finally, we present a two-stage stimulus design procedure which combines the dual goals of model estimation and model comparison and may be especially useful for system identification experiments where the appropriate model is unknown beforehand. We propose that fast, on-line stimulus optimization enabled by increasing computer power can make it practical to move sensory neuroscience away from a descriptive paradigm and toward a new paradigm of real-time model estimation and comparison. PMID:23761737

  18. Linear system identification - The application of Lion's identification scheme to a third order system with noisy input-output measurements

    NASA Technical Reports Server (NTRS)

    Brown, C. M., Jr.; Monopoli, R. V.

    1974-01-01

    A linear system identification technique developed by Lion is adapted for use on a third-order system with six unknown parameters and noisy input-output measurements. A digital computer is employed so that rapid identification takes place with only two state variable filters. Bias in the parameter estimates is partially eliminated by a signal-to-noise ratio testing procedure.

  19. Temporal adaptability and the inverse relationship to sensitivity: a parameter identification model.

    PubMed

    Langley, Keith

    2005-01-01

    Following a prolonged period of visual adaptation to a temporally modulated sinusoidal luminance pattern, the threshold contrast of a similar visual pattern is elevated. The adaptive elevation in threshold contrast is selective for spatial frequency, may saturate at low adaptor contrast, and increases as a function of the spatio-temporal frequency of the adapting signal. A model for signal extraction that is capable of explaining these threshold contrast effects of adaptation is proposed. Contrast adaptation in the model is explained by the identification of the parameters of an environmental model: the autocorrelation function of the visualized signal. The proposed model predicts that the adaptability of threshold contrast is governed by unpredicted signal variations present in the visual signal, and thus represents an internal adjustment by the visual system that takes into account these unpredicted signal variations given the additional possibility for signal corruption by additive noise.

  20. Nanosatellite Launch Adapter System (NLAS)

    NASA Technical Reports Server (NTRS)

    Yost, Bruce D.; Hines, John W.; Agasid, Elwood F.; Buckley, Steven J.

    2010-01-01

    The utility of small spacecraft based on the University cubesat standard is becoming evident as more and more agencies and organizations are launching or planning to include nanosatellites in their mission portfolios. Cubesats are typically launched as secondary spacecraft in enclosed, containerized deployers such as the CalPoly Poly Picosat Orbital Deployer (P-POD) system. The P-POD allows for ease of integration and significantly reduces the risk exposure to the primary spacecraft and mission. NASA/ARC and the Operationally Responsive Space office are collaborating to develop a Nanosatellite Launch Adapter System (NLAS), which can accommodate multiple cubesat or cubesat-derived spacecraft on a single launch vehicle. NLAS is composed of the adapter structure, P-POD or similar spacecraft dispensers, and a sequencer/deployer system. This paper describes the NLAS system and it s future capabilities, and also provides status on the system s development and potential first use in space.

  1. Adaptive bioinspired landmark identification for navigation control

    NASA Astrophysics Data System (ADS)

    Arena, Paolo; Cruse, Holk; Fortuna, Luigi; Lombardo, Davide; Patané, Luca; Rapisarda, Rosa

    2007-05-01

    In this paper a new methodology for landmark navigation will be introduced. Either for animals or for artificial agents, the whole problem of landmark navigation can be divided into two parts: first, the agent has to recognize, from the dynamic environment, space invariant objects which can be considered as suitable landmarks for driving the motion towards a goal position; second, it has to use the information on the landmarks to effectively navigate within the environment. Here, the problem of determining landmarks has been addressed by processing the external information through a spiking network with dynamic synapses plastically tuned by an STDP algorithm. The learning processes establish correlations between the incoming stimuli, allowing the system to extract from the scenario important features which can play the role of landmarks. Once established the landmarks, the agent acquires geometric relationships between them and the goal position. This process defines the parameters of a recurrent neural network (RNN). This in turn drives the agent navigation, filtering the information about landmarks given within an absolute reference system (e.g the North). When the absolute reference is not available, a safety mechanism acts to control the motion maintaining a correct heading. Simulation results showed the potentiality of the proposed architecture: this is able to drive an agent towards the desired position in presence of stimuli subject to noise and also in the case of partially obscured landmarks.

  2. Adaptive control based on fast online algebraic identification and GPI control for magnetic levitation systems with time-varying input gain

    NASA Astrophysics Data System (ADS)

    Morales, R.; Sira-Ramírez, H.; Feliu, V.

    2014-08-01

    This paper considers the position tracking problem of a voltage-controlled magnetic levitation system (MLS) in the presence of modelling errors caused by uncertainties in the system's physical parameters. An adaptive control based on fast online algebraic parameter estimation and generalised proportional integral (GPI) output feedback control is considered as a control scheme candidate. The GPI controller guarantees an asymptotically exponentially stable behaviour of the controlled ball position and the possibilities of carrying out rest-to-rest trajectory tracking tasks. The nature of the control input gain in an MLS is that of a state-dependent time-varying gain, reflecting the nonlinear character of the magnetic force with regard to the distance and the properties of the metallic ball. The system gain has therefore been locally approximated using a periodically updated time polynomial function (of second degree), where the coefficients of the polynomial are estimated during a very short period of time. This estimation is achieved using the recently introduced algebraic online parameter estimation approach. The stability of the closed-loop system is demonstrated under the assumption that no external factors cause changes in the parameter during the time interval in which the stability is analysed. Finally, experimental results are presented for the controlled MLS demonstrating the excellent stabilisation and position tracking performance of the control system designed in the presence of significant nonlinearities and uncertainties of the underlying system.

  3. Architecture for Adaptive Intelligent Systems

    NASA Technical Reports Server (NTRS)

    Hayes-Roth, Barbara

    1993-01-01

    We identify a class of niches to be occupied by 'adaptive intelligent systems (AISs)'. In contrast with niches occupied by typical AI agents, AIS niches present situations that vary dynamically along several key dimensions: different combinations of required tasks, different configurations of available resources, contextual conditions ranging from benign to stressful, and different performance criteria. We present a small class hierarchy of AIS niches that exhibit these dimensions of variability and describe a particular AIS niche, ICU (intensive care unit) patient monitoring, which we use for illustration throughout the paper. We have designed and implemented an agent architecture that supports all of different kinds of adaptation by exploiting a single underlying theoretical concept: An agent dynamically constructs explicit control plans to guide its choices among situation-triggered behaviors. We illustrate the architecture and its support for adaptation with examples from Guardian, an experimental agent for ICU monitoring.

  4. The Limits to Adaptation; A Systems Approach

    EPA Science Inventory

    The Limits to Adaptation: A Systems Approach. The ability to adapt to climate change is delineated by capacity thresholds, after which climate damages begin to overwhelm the adaptation response. Such thresholds depend upon physical properties (natural processes and engineering...

  5. The Identification of Lymphocyte-Like Cells and Lymphoid-Related Genes in Amphioxus Indicates the Twilight for the Emergency of Adaptive Immune System

    PubMed Central

    Huang, Gonghua; Xie, Xiaojin; Han, Yan; Fan, Lifei; Chen, Jie; Mou, Chunyan; Guo, Lei; Liu, Hui; Zhang, Qinfen; Chen, Shangwu; Dong, Meiling; Liu, Jianzhong; Xu, Anlong

    2007-01-01

    To seek evidence of a primitive adaptive immune system (AIS) before vertebrate, we examined whether lymphocytes or lymphocyte-like cells and the related molecules participating in the lymphocyte function existed in amphioxus. Anatomical analysis by electron microscopy revealed the presence of lymphocyte-like cells in gills, and these cells underwent morphological changes in response to microbial pathogens that are reminiscent of those of mammalian lymphocytes executing immune response to microbial challenge. In addition, a systematic comparative analysis of our cDNA database of amphioxus identified a large number of genes whose vertebrate counterparts are involved in lymphocyte function. Among these genes, several genes were found to be expressed in the vicinity of the lymphocyte-like cells by in situ hybridization and up-regulated after exposure to microbial pathogens. Our findings in the amphioxus indicate the twilight for the emergency of AIS before the invertebrate-vertebrate transition during evolution. PMID:17299586

  6. Multisensor fusion for system identification

    NASA Astrophysics Data System (ADS)

    Sim, Sung-Han; Cho, Soojin; Park, Jong-Woong; Kim, Hyunjun

    2014-04-01

    System identification is a fundamental process for developing a numerical model of a physical structure. The system identification process typically involves in data acquisition; particularly in civil engineering applications accelerometers are preferred due to its cost-effectiveness, low noise, and installation convenience. Because the measured acceleration responses result in translational degrees of freedom (DOF) in the numerical model, moment-resisting structures such as beam and plate are not appropriately represented by the models. This study suggests a system identification process that considers both translational and rotational DOFs by using accelerometers and gyroscopes. The proposed approach suggests a systematic way of obtaining dynamic characteristics as well as flexibility matrix from two different measurements of acceleration and angular velocity. Numerical simulation and laboratory experiment are conducted to validate the efficacy of the proposed system identification process.

  7. Certification Considerations for Adaptive Systems

    NASA Technical Reports Server (NTRS)

    Bhattacharyya, Siddhartha; Cofer, Darren; Musliner, David J.; Mueller, Joseph; Engstrom, Eric

    2015-01-01

    Advanced capabilities planned for the next generation of aircraft, including those that will operate within the Next Generation Air Transportation System (NextGen), will necessarily include complex new algorithms and non-traditional software elements. These aircraft will likely incorporate adaptive control algorithms that will provide enhanced safety, autonomy, and robustness during adverse conditions. Unmanned aircraft will operate alongside manned aircraft in the National Airspace (NAS), with intelligent software performing the high-level decision-making functions normally performed by human pilots. Even human-piloted aircraft will necessarily include more autonomy. However, there are serious barriers to the deployment of new capabilities, especially for those based upon software including adaptive control (AC) and artificial intelligence (AI) algorithms. Current civil aviation certification processes are based on the idea that the correct behavior of a system must be completely specified and verified prior to operation. This report by Rockwell Collins and SIFT documents our comprehensive study of the state of the art in intelligent and adaptive algorithms for the civil aviation domain, categorizing the approaches used and identifying gaps and challenges associated with certification of each approach.

  8. Adaptive Intrusion Data System (AIDS)

    SciTech Connect

    Corlis, N. E.

    1980-05-01

    The adaptive intrusion data system (AIDS) was developed to collect data from intrusion alarm sensors as part of an evaluation system to improve sensor performance. AIDS is a unique data system which uses computer controlled data systems, video cameras and recorders, analog-to-digital conversion, environmental sensors, and digital recorders to collect sensor data. The data can be viewed either manually or with a special computerized data-reduction system which adds new data to a data base stored on a magnetic disc recorder. This report provides a synoptic account of the AIDS as it presently exists. Modifications to the purchased subsystems are described, and references are made to publications which describe the Sandia-designed subsystems.

  9. The ERIS adaptive optics system

    NASA Astrophysics Data System (ADS)

    Marchetti, Enrico; Fedrigo, Enrico; Le Louarn, Miska; Madec, Pierre-Yves; Soenke, Christian; Brast, Roland; Conzelmann, Ralf; Delabre, Bernard; Duchateau, Michel; Frank, Christoph; Klein, Barbara; Amico, Paola; Hubin, Norbert; Esposito, Simone; Antichi, Jacopo; Carbonaro, Luca; Puglisi, Alfio; Quirós-Pacheco, Fernando; Riccardi, Armando; Xompero, Marco

    2014-07-01

    The Enhanced Resolution Imager and Spectrograph (ERIS) is the new Adaptive Optics based instrument for ESO's VLT aiming at replacing NACO and SINFONI to form a single compact facility with AO fed imaging and integral field unit spectroscopic scientific channels. ERIS completes the instrument suite at the VLT adaptive telescope. In particular it is equipped with a versatile AO system that delivers up to 95% Strehl correction in K band for science observations up to 5 micron It comprises high order NGS and LGS correction enabling the observation from exoplanets to distant galaxies with a large sky coverage thanks to the coupling of the LGS WFS with the high sensitivity of its visible WFS and the capability to observe in dust embedded environment thanks to its IR low order WFS. ERIS will be installed at the Cassegrain focus of the VLT unit hosting the Adaptive Optics Facility (AOF). The wavefront correction is provided by the AOF deformable secondary mirror while the Laser Guide Star is provided by one of the four launch units of the 4 Laser Guide Star Facility for the AOF. The overall layout of the ERIS AO system is extremely compact and highly optimized: the SPIFFI spectrograph is fed directly by the Cassegrain focus and both the NIX's (IR imager) and SPIFFI's entrance windows work as visible/infrared dichroics. In this paper we describe the concept of the ERIS AO system in detail, starting from the requirements and going through the estimated performance, the opto-mechanical design and the Real-Time Computer design.

  10. Adaptive Behaviour Assessment System: Indigenous Australian Adaptation Model (ABAS: IAAM)

    ERIC Educational Resources Information Center

    du Plessis, Santie

    2015-01-01

    The study objectives were to develop, trial and evaluate a cross-cultural adaptation of the Adaptive Behavior Assessment System-Second Edition Teacher Form (ABAS-II TF) ages 5-21 for use with Indigenous Australian students ages 5-14. This study introduced a multiphase mixed-method design with semi-structured and informal interviews, school…

  11. Adaptable state based control system

    NASA Technical Reports Server (NTRS)

    Rasmussen, Robert D. (Inventor); Dvorak, Daniel L. (Inventor); Gostelow, Kim P. (Inventor); Starbird, Thomas W. (Inventor); Gat, Erann (Inventor); Chien, Steve Ankuo (Inventor); Keller, Robert M. (Inventor)

    2004-01-01

    An autonomous controller, comprised of a state knowledge manager, a control executor, hardware proxies and a statistical estimator collaborates with a goal elaborator, with which it shares common models of the behavior of the system and the controller. The elaborator uses the common models to generate from temporally indeterminate sets of goals, executable goals to be executed by the controller. The controller may be updated to operate in a different system or environment than that for which it was originally designed by the replacement of shared statistical models and by the instantiation of a new set of state variable objects derived from a state variable class. The adaptation of the controller does not require substantial modification of the goal elaborator for its application to the new system or environment.

  12. Self-adaptive Vision System

    NASA Astrophysics Data System (ADS)

    Stipancic, Tomislav; Jerbic, Bojan

    Light conditions represent an important part of every vision application. This paper describes one active behavioral scheme of one particular active vision system. This behavioral scheme enables an active system to adapt to current environmental conditions by constantly validating the amount of the reflected light using luminance meter and dynamically changed significant vision parameters. The purpose of the experiment was to determine the connections between light conditions and inner vision parameters. As a part of the experiment, Response Surface Methodology (RSM) was used to predict values of vision parameters with respect to luminance input values. RSM was used to approximate an unknown function for which only few values were computed. The main output validation system parameter is called Match Score. Match Score indicates how well the found object matches the learned model. All obtained data are stored in the local database. By timely applying new parameters predicted by the RSM, the vision application works in a stabile and robust manner.

  13. Integration of Online Parameter Identification and Neural Network for In-Flight Adaptive Control

    NASA Technical Reports Server (NTRS)

    Hageman, Jacob J.; Smith, Mark S.; Stachowiak, Susan

    2003-01-01

    An indirect adaptive system has been constructed for robust control of an aircraft with uncertain aerodynamic characteristics. This system consists of a multilayer perceptron pre-trained neural network, online stability and control derivative identification, a dynamic cell structure online learning neural network, and a model following control system based on the stochastic optimal feedforward and feedback technique. The pre-trained neural network and model following control system have been flight-tested, but the online parameter identification and online learning neural network are new additions used for in-flight adaptation of the control system model. A description of the modification and integration of these two stand-alone software packages into the complete system in preparation for initial flight tests is presented. Open-loop results using both simulation and flight data, as well as closed-loop performance of the complete system in a nonlinear, six-degree-of-freedom, flight validated simulation, are analyzed. Results show that this online learning system, in contrast to the nonlearning system, has the ability to adapt to changes in aerodynamic characteristics in a real-time, closed-loop, piloted simulation, resulting in improved flying qualities.

  14. The experimental results of a self tuning adaptive controller using online frequency identification. [for Galileo spacecraft

    NASA Technical Reports Server (NTRS)

    Chiang, W.-W.; Cannon, R. H., Jr.

    1985-01-01

    A fourth-order laboratory dynamic system featuring very low structural damping and a noncolocated actuator-sensor pair has been used to test a novel real-time adaptive controller, implemented in a minicomputer, which consists of a state estimator, a set of state feedback gains, and a frequency-locked loop for real-time parameter identification. The adaptation algorithm employed can correct controller error and stabilize the system for more than 50 percent variation in the plant's natural frequency, compared with a 10 percent stability margin in frequency variation for a fixed gain controller having the same performance as the nominal plant condition. The very rapid convergence achievable by this adaptive system is demonstrated experimentally, and proven with simple, root-locus methods.

  15. Systems identification - reprise and projections

    NASA Technical Reports Server (NTRS)

    Taylor, L. W., Jr.

    1974-01-01

    A state-of-the-arts review is given for the field of system identification. Progress in the field is traced from the early models of dynamic systems by Sir Isaac Newton up to the present day use of advanced techniques for numerous applications.

  16. Adaptive Similarity Measures for Material Identification in Hyperspectral Imagery

    NASA Astrophysics Data System (ADS)

    Bue, Brian D.

    Remotely-sensed hyperspectral imagery has become one the most advanced tools for analyzing the processes that shape the Earth and other planets. Effective, rapid analysis of high-volume, high-dimensional hyperspectral image data sets demands efficient, automated techniques to identify signatures of known materials in such imagery. In this thesis, we develop a framework for automatic material identification in hyperspectral imagery using adaptive similarity measures. We frame the material identification problem as a multiclass similarity-based classification problem, where our goal is to predict material labels for unlabeled target spectra based upon their similarities to source spectra with known material labels. As differences in capture conditions affect the spectral representations of materials, we divide the material identification problem into intra-domain (i.e., source and target spectra captured under identical conditions) and inter-domain (i.e., source and target spectra captured under different conditions) settings. The first component of this thesis develops adaptive similarity measures for intra-domain settings that measure the relevance of spectral features to the given classification task using small amounts of labeled data. We propose a technique based on multiclass Linear Discriminant Analysis (LDA) that combines several distinct similarity measures into a single hybrid measure capturing the strengths of each of the individual measures. We also provide a comparative survey of techniques for low-rank Mahalanobis metric learning, and demonstrate that regularized LDA yields competitive results to the state-of-the-art, at substantially lower computational cost. The second component of this thesis shifts the focus to inter-domain settings, and proposes a multiclass domain adaptation framework that reconciles systematic differences between spectra captured under similar, but not identical, conditions. Our framework computes a similarity-based mapping that

  17. Identification and dual adaptive control of a turbojet engine

    NASA Technical Reports Server (NTRS)

    Merrill, W.; Leininger, G.

    1979-01-01

    The objective of this paper is to utilize the design methods of modern control theory to realize a dual-adaptive feedback control unit for a highly nonlinear single spool airbreathing turbojet engine. Using a very detailed and accurate simulation of the nonlinear engine as the data source, linear operating point models of unspecified dimension are identified. Feedback control laws are designed at each operating point for a prespecified set of sampling rates using sampled-data output regulator theory. The control system sampling rate is determined by an adaptive sampling algorithm in correspondence with turbojet engine performance. The result is a dual-adaptive control law that is functionally dependent upon the sampling rate selected and environmental operating conditions. Simulation transients demonstrate the utility of the dual-adaptive design to improve on-board computer utilization while maintaining acceptable levels of engine performance.

  18. Electricity Market Complex Adaptive System

    2004-10-14

    EMCAS is a model developed for the simulation and analysis of electricity markets. As power markets are relatively new and still continue to evolve, there is a growing need for advanced modeling approaches that simulate the behavior of electricity markets over time and how market participants may act and react to the changing economic, financial, and regulatory environments in which they operate. A new and rather promising approach applied in the EMCAS software is tomore » model the electricity market as a complex adaptive system using an agent-based modeling and simulation scheme. With its unique combination of various novel approaches, the Agent Based Modeling System (ABMS) provides the ability to capture and investigate the complex interactions between the physical infrastructures (generation, transmission, and distribution) and the economic behavior of market participants that are a trademark of the newly emerging markets.« less

  19. Advances in rotorcraft system identification

    NASA Astrophysics Data System (ADS)

    Hamel, Peter G.; Kaletka, Jürgen

    1997-03-01

    System identification can best be described as the extraction of system characteristics from measured flight test data. Therefore it provides an excellent tool for determining and improving mathematical models for a wide range of applications. The increasing need for accurate models for the design of high bandwidth control systems for rotorcraft has initiated a high interest in and a more intensive use of system identification. This development was supported by the AGARD FVP Working Group 18 on ‘Rotorcraft System Identification’, which brought together specialists from research organisations and industry, tasked with exploring the potential of this tool. In the Group, the full range of identification approaches was applied to dedicated helicopter flight-test-data including data quality checking and the determination and verification of flight mechanical models. It was mainly concentrated on the identification of six degrees of freedom rigid body models, which provide a realistic description of the rotorcraft dynamics for the lower and medium frequency range. The accomplishment of the Working Group has increased the demand for applying these techniques more routinely and, in addition, for extending the model order by including explicit rotor degrees of freedom. Such models also accurately characterize the higher frequency range needed for high bandwidth control system designs. In the specific case of the DLR In-Flight Simulator BO 105 ATTHeS, the application of the identified higher order models for the model-following control system was a major prerequisite for the obtained high simulation quality.

  20. Towards the identification of the loci of adaptive evolution

    PubMed Central

    Pardo-Diaz, Carolina; Salazar, Camilo; Jiggins, Chris D

    2015-01-01

    1. Establishing the genetic and molecular basis underlying adaptive traits is one of the major goals of evolutionary geneticists in order to understand the connection between genotype and phenotype and elucidate the mechanisms of evolutionary change. Despite considerable effort to address this question, there remain relatively few systems in which the genes shaping adaptations have been identified. 2. Here, we review the experimental tools that have been applied to document the molecular basis underlying evolution in several natural systems, in order to highlight their benefits, limitations and suitability. In most cases, a combination of DNA, RNA and functional methodologies with field experiments will be needed to uncover the genes and mechanisms shaping adaptation in nature. PMID:25937885

  1. Automated drug identification system

    NASA Technical Reports Server (NTRS)

    Campen, C. F., Jr.

    1974-01-01

    System speeds up analysis of blood and urine and is capable of identifying 100 commonly abused drugs. System includes computer that controls entire analytical process by ordering various steps in specific sequences. Computer processes data output and has readout of identified drugs.

  2. Emergent system identification using particle swarm optimization

    NASA Astrophysics Data System (ADS)

    Voss, Mark S.; Feng, Xin

    2001-10-01

    Complex Adaptive Structures can be viewed as a combination of Complex Adaptive Systems and fully integrated autonomous Smart Structures. Traditionally when designing a structure, one combines rules of thumb with theoretical results to develop an acceptable solution. This methodology will have to be extended for Complex Adaptive Structures, since they, by definition, will participate in their own design. In this paper we introduce a new methodology for Emergent System Identification that is concerned with combining the methodologies of self-organizing functional networks (GMDH - Alexy G. Ivakhnenko), Particle Swarm Optimization (PSO - James Kennedy and Russell C. Eberhart) and Genetic Programming (GP - John Koza). This paper will concentrate on the utilization of Particle Swarm Optimization in this effort and discuss how Particle Swarm Optimization relates to our ultimate goal of emergent self-organizing functional networks that can be used to identify overlapping internal structural models. The ability for Complex Adaptive Structures to identify emerging internal models will be a key component for their success.

  3. Fast Source Camera Identification Using Content Adaptive Guided Image Filter.

    PubMed

    Zeng, Hui; Kang, Xiangui

    2016-03-01

    Source camera identification (SCI) is an important topic in image forensics. One of the most effective fingerprints for linking an image to its source camera is the sensor pattern noise, which is estimated as the difference between the content and its denoised version. It is widely believed that the performance of the sensor-based SCI heavily relies on the denoising filter used. This study proposes a novel sensor-based SCI method using content adaptive guided image filter (CAGIF). Thanks to the low complexity nature of the CAGIF, the proposed method is much faster than the state-of-the-art methods, which is a big advantage considering the potential real-time application of SCI. Despite the advantage of speed, experimental results also show that the proposed method can achieve comparable or better performance than the state-of-the-art methods in terms of accuracy. PMID:27404627

  4. Identification and dual adaptive control of a turbojet engine

    NASA Technical Reports Server (NTRS)

    Merrill, W.; Leininger, G.

    1979-01-01

    The objective of this paper is to utilize the design methods of modern control theory to realize a 'dual-adaptive' feedback control unit for a highly non-linear single spool airbreathing turbojet engine. Using a very detailed and accurate simulation of the non-linear engine as the data source, linear operating point models of unspecified dimension are identified. Feedback control laws are designed at each operating point for a prespecified set of sampling rates using sampled-data output regulator theory. The control system sampling rate is determined by an adaptive sampling algorithm in correspondence with turbojet engine performance. The result is a 'dual-adpative' control law that is functionally dependent upon the sampling rate selected and environmental operating conditions. Simulation transients demonstrate the utility of the dual-adaptive design to improve on-board computer utilization while maintaining acceptable levels of engine performance.

  5. Adaptive identification and interpretation of pressure transient tests of horizontal wells: challenges and perspectives

    NASA Astrophysics Data System (ADS)

    Sergeev, V. L.; Van Hoang, Dong

    2016-09-01

    The paper deals with a topical issue of defining oil reservoir properties during transient tests of horizontal wells equipped with information-measuring systems and reducing well downtime. The aim is to consider challenges and perspectives of developing models and algorithms for adaptive identification and interpretation of transient tests in horizontal wells with pressure buildup curve analysis. The models and algorithms should allow analyzing flow behavior, defining oil reservoir properties and determining well test completion time, as well as reducing well downtime. The present paper is based on the previous theoretical and practical findings in the spheres of transient well testing, systems analysis, system identification, function optimization and linear algebra. Field data and results of transient well tests with pressure buildup curve analysis have also been considered. The suggested models and algorithms for adaptive interpretation of transient tests conducted in horizontal wells with resulting pressure buildup curve make it possible to analyze flow behavior, as well as define the reservoir properties and determine well test completion time. The algorithms for adaptive interpretation are based on the integrated system of radial flow PBC models with time- dependent variables, account of additional a priori information and estimates of radial flow permeability. Optimization problems are solved with the case study of PBC interpretation for five horizontal wells of the Verkhnechonsk field.

  6. A bimodal biometric identification system

    NASA Astrophysics Data System (ADS)

    Laghari, Mohammad S.; Khuwaja, Gulzar A.

    2013-03-01

    Biometrics consists of methods for uniquely recognizing humans based upon one or more intrinsic physical or behavioral traits. Physicals are related to the shape of the body. Behavioral are related to the behavior of a person. However, biometric authentication systems suffer from imprecision and difficulty in person recognition due to a number of reasons and no single biometrics is expected to effectively satisfy the requirements of all verification and/or identification applications. Bimodal biometric systems are expected to be more reliable due to the presence of two pieces of evidence and also be able to meet the severe performance requirements imposed by various applications. This paper presents a neural network based bimodal biometric identification system by using human face and handwritten signature features.

  7. Structural Aspects of System Identification

    NASA Technical Reports Server (NTRS)

    Glover, Keith

    1973-01-01

    The problem of identifying linear dynamical systems is studied by considering structural and deterministic properties of linear systems that have an impact on stochastic identification algorithms. In particular considered is parametrization of linear systems so that there is a unique solution and all systems in appropriate class can be represented. It is assumed that a parametrization of system matrices has been established from a priori knowledge of the system, and the question is considered of when the unknown parameters of this system can be identified from input/output observations. It is assumed that the transfer function can be asymptotically identified, and the conditions are derived for the local, global and partial identifiability of the parametrization. Then it is shown that, with the right formulation, identifiability in the presence of feedback can be treated in the same way. Similarly the identifiability of parametrizations of systems driven by unobserved white noise is considered using the results from the theory of spectral factorization.

  8. Modeling Power Systems as Complex Adaptive Systems

    SciTech Connect

    Chassin, David P.; Malard, Joel M.; Posse, Christian; Gangopadhyaya, Asim; Lu, Ning; Katipamula, Srinivas; Mallow, J V.

    2004-12-30

    Physical analogs have shown considerable promise for understanding the behavior of complex adaptive systems, including macroeconomics, biological systems, social networks, and electric power markets. Many of today's most challenging technical and policy questions can be reduced to a distributed economic control problem. Indeed, economically based control of large-scale systems is founded on the conjecture that the price-based regulation (e.g., auctions, markets) results in an optimal allocation of resources and emergent optimal system control. This report explores the state-of-the-art physical analogs for understanding the behavior of some econophysical systems and deriving stable and robust control strategies for using them. We review and discuss applications of some analytic methods based on a thermodynamic metaphor, according to which the interplay between system entropy and conservation laws gives rise to intuitive and governing global properties of complex systems that cannot be otherwise understood. We apply these methods to the question of how power markets can be expected to behave under a variety of conditions.

  9. [Adaptation of the avidin-biotin system for identifying and quantifying Sendai virus antigens].

    PubMed

    Popa, L M; Marcheş, F; Repanovici, R; Iliescu, R; Muţiu, A; Cajal, N

    1989-01-01

    The avidin-biotin system was adapted in view of the identification and dosage of the Sendai parainfluenza virus and of its antigens, using the method of double antibodies (biotinylated and nonbiotinylated) in ELISA type tests. PMID:2549703

  10. Suppression Measured from Chinchilla Auditory-Nerve-Fiber Responses Following Noise-Induced Hearing Loss: Adaptive-Tracking and Systems-Identification Approaches

    PubMed Central

    Sayles, Mark; Walls, Michael K.

    2016-01-01

    The compressive nonlinearity of cochlear signal transduction, reflecting outer-hair-cell function, manifests as suppressive spectral interactions; e.g., two-tone suppression. Moreover, for broadband sounds, there are multiple interactions between frequency components. These frequency-dependent nonlinearities are important for neural coding of complex sounds, such as speech. Acoustic-trauma-induced outer-hair-cell damage is associated with loss of nonlinearity, which auditory prostheses attempt to restore with, e.g., “multi-channel dynamic compression” algorithms. Neurophysiological data on suppression in hearing-impaired (HI) mammals are limited. We present data on firing-rate suppression measured in auditory-nerve-fiber responses in a chinchilla model of noise-induced hearing loss, and in normal-hearing (NH) controls at equal sensation level. Hearing-impaired (HI) animals had elevated single-fiber excitatory thresholds (by ~ 20–40 dB), broadened frequency tuning, and reduced-magnitude distortion-product otoacoustic emissions; consistent with mixed inner- and outer-hair-cell pathology. We characterized suppression using two approaches: adaptive tracking of two-tone-suppression threshold (62 NH, and 35 HI fibers), and Wiener-kernel analyses of responses to broadband noise (91 NH, and 148 HI fibers). Suppression-threshold tuning curves showed sensitive low-side suppression for NH and HI animals. High-side suppression thresholds were elevated in HI animals, to the same extent as excitatory thresholds. We factored second-order Wiener-kernels into excitatory and suppressive sub-kernels to quantify the relative strength of suppression. We found a small decrease in suppression in HI fibers, which correlated with broadened tuning. These data will help guide novel amplification strategies, particularly for complex listening situations (e.g., speech in noise), in which current hearing aids struggle to restore intelligibility. PMID:27080669

  11. Suppression Measured from Chinchilla Auditory-Nerve-Fiber Responses Following Noise-Induced Hearing Loss: Adaptive-Tracking and Systems-Identification Approaches.

    PubMed

    Sayles, Mark; Walls, Michael K; Heinz, Michael G

    2016-01-01

    The compressive nonlinearity of cochlear signal transduction, reflecting outer-hair-cell function, manifests as suppressive spectral interactions; e.g., two-tone suppression. Moreover, for broadband sounds, there are multiple interactions between frequency components. These frequency-dependent nonlinearities are important for neural coding of complex sounds, such as speech. Acoustic-trauma-induced outer-hair-cell damage is associated with loss of nonlinearity, which auditory prostheses attempt to restore with, e.g., "multi-channel dynamic compression" algorithms.Neurophysiological data on suppression in hearing-impaired (HI) mammals are limited. We present data on firing-rate suppression measured in auditory-nerve-fiber responses in a chinchilla model of noise-induced hearing loss, and in normal-hearing (NH) controls at equal sensation level. Hearing-impaired (HI) animals had elevated single-fiber excitatory thresholds (by ~ 20-40 dB), broadened frequency tuning, and reduced-magnitude distortion-product otoacoustic emissions; consistent with mixed inner- and outer-hair-cell pathology. We characterized suppression using two approaches: adaptive tracking of two-tone-suppression threshold (62 NH, and 35 HI fibers), and Wiener-kernel analyses of responses to broadband noise (91 NH, and 148 HI fibers). Suppression-threshold tuning curves showed sensitive low-side suppression for NH and HI animals. High-side suppression thresholds were elevated in HI animals, to the same extent as excitatory thresholds. We factored second-order Wiener-kernels into excitatory and suppressive sub-kernels to quantify the relative strength of suppression. We found a small decrease in suppression in HI fibers, which correlated with broadened tuning. These data will help guide novel amplification strategies, particularly for complex listening situations (e.g., speech in noise), in which current hearing aids struggle to restore intelligibility. PMID:27080669

  12. Suppression Measured from Chinchilla Auditory-Nerve-Fiber Responses Following Noise-Induced Hearing Loss: Adaptive-Tracking and Systems-Identification Approaches.

    PubMed

    Sayles, Mark; Walls, Michael K; Heinz, Michael G

    2016-01-01

    The compressive nonlinearity of cochlear signal transduction, reflecting outer-hair-cell function, manifests as suppressive spectral interactions; e.g., two-tone suppression. Moreover, for broadband sounds, there are multiple interactions between frequency components. These frequency-dependent nonlinearities are important for neural coding of complex sounds, such as speech. Acoustic-trauma-induced outer-hair-cell damage is associated with loss of nonlinearity, which auditory prostheses attempt to restore with, e.g., "multi-channel dynamic compression" algorithms.Neurophysiological data on suppression in hearing-impaired (HI) mammals are limited. We present data on firing-rate suppression measured in auditory-nerve-fiber responses in a chinchilla model of noise-induced hearing loss, and in normal-hearing (NH) controls at equal sensation level. Hearing-impaired (HI) animals had elevated single-fiber excitatory thresholds (by ~ 20-40 dB), broadened frequency tuning, and reduced-magnitude distortion-product otoacoustic emissions; consistent with mixed inner- and outer-hair-cell pathology. We characterized suppression using two approaches: adaptive tracking of two-tone-suppression threshold (62 NH, and 35 HI fibers), and Wiener-kernel analyses of responses to broadband noise (91 NH, and 148 HI fibers). Suppression-threshold tuning curves showed sensitive low-side suppression for NH and HI animals. High-side suppression thresholds were elevated in HI animals, to the same extent as excitatory thresholds. We factored second-order Wiener-kernels into excitatory and suppressive sub-kernels to quantify the relative strength of suppression. We found a small decrease in suppression in HI fibers, which correlated with broadened tuning. These data will help guide novel amplification strategies, particularly for complex listening situations (e.g., speech in noise), in which current hearing aids struggle to restore intelligibility.

  13. On-Orbit System Identification

    NASA Technical Reports Server (NTRS)

    Mettler, E.; Milman, M. H.; Bayard, D.; Eldred, D. B.

    1987-01-01

    Information derived from accelerometer readings benefits important engineering and control functions. Report discusses methodology for detection, identification, and analysis of motions within space station. Techniques of vibration and rotation analyses, control theory, statistics, filter theory, and transform methods integrated to form system for generating models and model parameters that characterize total motion of complicated space station, with respect to both control-induced and random mechanical disturbances.

  14. Visual Cues for an Adaptive Expert System.

    ERIC Educational Resources Information Center

    Miller, Helen B.

    NCR (National Cash Register) Corporation is pursuing opportunities to make their point of sale (POS) terminals easy to use and easy to learn. To approach the goal of making the technology invisible to the user, NCR has developed an adaptive expert prototype system for a department store POS operation. The structure for the adaptive system, the…

  15. Automated systems for identification of microorganisms.

    PubMed Central

    Stager, C E; Davis, J R

    1992-01-01

    Automated instruments for the identification of microorganisms were introduced into clinical microbiology laboratories in the 1970s. During the past two decades, the capabilities and performance characteristics of automated identification systems have steadily progressed and improved. This article explores the development of the various automated identification systems available in the United States and reviews their performance for identification of microorganisms. Observations regarding deficiencies and suggested improvements for these systems are provided. PMID:1498768

  16. System identification of Drosophila olfactory sensory neurons.

    PubMed

    Kim, Anmo J; Lazar, Aurel A; Slutskiy, Yevgeniy B

    2011-02-01

    , for a fixed mean of the odor waveform, independent of the stimulus contrast. This suggests that white noise system identification of Or59b OSNs only depends on the first moment of the odor concentration. Finally, by comparing the 2D Encoding Manifold and the 2D LNP model, we demonstrate that the OSN identification results depend on the particular type of the employed test odor waveforms. This suggests an adaptive neural encoding model for Or59b OSNs that changes its nonlinearity in response to the odor concentration waveforms.

  17. Adaptation with disturbance attenuation in nonlinear control systems

    SciTech Connect

    Basar, T.

    1997-12-31

    We present an optimization-based adaptive controller design for nonlinear systems exhibiting parametric as well as functional uncertainty. The approach involves the formulation of an appropriate cost functional that places positive weight on deviations from the achievement of desired objectives (such as tracking of a reference trajectory while the system exhibits good transient performance) and negative weight on the energy of the uncertainty. This cost functional also translates into a disturbance attenuation inequality which quantifies the effect of the presence of uncertainty on the desired objective, which in turn yields an interpretation for the optimizing control as one that optimally attenuates the disturbance, viewed as the collection of unknown parameters and unknown signals entering the system dynamics. In addition to this disturbance attenuation property, the controllers obtained also feature adaptation in the sense that they help with identification of the unknown parameters, even though this has not been set as the primary goal of the design. In spite of this adaptation/identification role, the controllers obtained are not of certainty-equivalent type, which means that the identification and the control phases of the design are not decoupled.

  18. The MICE Particle Identification System

    NASA Astrophysics Data System (ADS)

    Bogomilov, M.; MICE Collaboration

    2011-06-01

    The Muon Ionization Cooling Experiment (MICE) at the ISIS accelerator located at the Rutherford Appleton Laboratory, UK, will be the first experiment to study muon cooling at high precision. Demonstration of muon ionization cooling is a major technological step towards the construction of a neutrino factory or a muon collider. A muon beam is produced via pion decay in the MICE beam line within a range of emittances and momenta. Muon purity is assured by a system of detectors for particle identification (PID). We describe briefly the PID system here.

  19. Evolutionary Adaptive Discovery of Phased Array Sensor Signal Identification

    SciTech Connect

    Timothy R. McJunkin; Milos Manic

    2011-05-01

    Tomography, used to create images of the internal properties and features of an object, from phased array ultasonics is improved through many sophisiticated methonds of post processing of data. One approach used to improve tomographic results is to prescribe the collection of more data, from different points of few so that data fusion might have a richer data set to work from. This approach can lead to rapid increase in the data needed to be stored and processed. It also does not necessarily lead to have the needed data. This article describes a novel approach to utilizing the data aquired as a basis for adapting the sensors focusing parameters to locate more precisely the features in the material: specifically, two evolutionary methods of autofocusing on a returned signal are coupled with the derivations of the forumulas for spatially locating the feature are given. Test results of the two novel methods of evolutionary based focusing (EBF) illustrate the improved signal strength and correction of the position of feature using the optimized focal timing parameters, called Focused Delay Identification (FoDI).

  20. On-orbit system parameter identification

    NASA Technical Reports Server (NTRS)

    Simonian, Stepan S.

    1988-01-01

    Viewgraphs and discussion on on-orbit system parameter identification are included. Topics covered include: dynamic programming filter (DPF); cost function and estimator; frequency domain formulation structrual dynamic identification; and attributes of DPF.

  1. Modern control concepts in hydrology. [parameter identification in adaptive stochastic control approach

    NASA Technical Reports Server (NTRS)

    Duong, N.; Winn, C. B.; Johnson, G. R.

    1975-01-01

    Two approaches to an identification problem in hydrology are presented, based upon concepts from modern control and estimation theory. The first approach treats the identification of unknown parameters in a hydrologic system subject to noisy inputs as an adaptive linear stochastic control problem; the second approach alters the model equation to account for the random part in the inputs, and then uses a nonlinear estimation scheme to estimate the unknown parameters. Both approaches use state-space concepts. The identification schemes are sequential and adaptive and can handle either time-invariant or time-dependent parameters. They are used to identify parameters in the Prasad model of rainfall-runoff. The results obtained are encouraging and confirm the results from two previous studies; the first using numerical integration of the model equation along with a trial-and-error procedure, and the second using a quasi-linearization technique. The proposed approaches offer a systematic way of analyzing the rainfall-runoff process when the input data are imbedded in noise.

  2. Input-output identification of controlled discrete manufacturing systems

    NASA Astrophysics Data System (ADS)

    Estrada-Vargas, Ana Paula; López-Mellado, Ernesto; Lesage, Jean-Jacques

    2014-03-01

    The automated construction of discrete event models from observations of external system's behaviour is addressed. This problem, often referred to as system identification, allows obtaining models of ill-known (or even unknown) systems. In this article, an identification method for discrete event systems (DESs) controlled by a programmable logic controller is presented. The method allows processing a large quantity of observed long sequences of input/output signals generated by the controller and yields an interpreted Petri net model describing the closed-loop behaviour of the automated DESs. The proposed technique allows the identification of actual complex systems because it is sufficiently efficient and well adapted to cope with both the technological characteristics of industrial controllers and data collection requirements. Based on polynomial-time algorithms, the method is implemented as an efficient software tool which constructs and draws the model automatically; an overview of this tool is given through a case study dealing with an automated manufacturing system.

  3. Adaptation in CRISPR-Cas Systems.

    PubMed

    Sternberg, Samuel H; Richter, Hagen; Charpentier, Emmanuelle; Qimron, Udi

    2016-03-17

    Clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated (Cas) proteins constitute an adaptive immune system in prokaryotes. The system preserves memories of prior infections by integrating short segments of foreign DNA, termed spacers, into the CRISPR array in a process termed adaptation. During the past 3 years, significant progress has been made on the genetic requirements and molecular mechanisms of adaptation. Here we review these recent advances, with a focus on the experimental approaches that have been developed, the insights they generated, and a proposed mechanism for self- versus non-self-discrimination during the process of spacer selection. We further describe the regulation of adaptation and the protein players involved in this fascinating process that allows bacteria and archaea to harbor adaptive immunity.

  4. An adaptive learning control system for large flexible structures

    NASA Technical Reports Server (NTRS)

    Thau, F. E.

    1985-01-01

    The objective of the research has been to study the design of adaptive/learning control systems for the control of large flexible structures. In the first activity an adaptive/learning control methodology for flexible space structures was investigated. The approach was based on using a modal model of the flexible structure dynamics and an output-error identification scheme to identify modal parameters. In the second activity, a least-squares identification scheme was proposed for estimating both modal parameters and modal-to-actuator and modal-to-sensor shape functions. The technique was applied to experimental data obtained from the NASA Langley beam experiment. In the third activity, a separable nonlinear least-squares approach was developed for estimating the number of excited modes, shape functions, modal parameters, and modal amplitude and velocity time functions for a flexible structure. In the final research activity, a dual-adaptive control strategy was developed for regulating the modal dynamics and identifying modal parameters of a flexible structure. A min-max approach was used for finding an input to provide modal parameter identification while not exceeding reasonable bounds on modal displacement.

  5. Highly integrated digital electronic control: Digital flight control, aircraft model identification, and adaptive engine control

    NASA Technical Reports Server (NTRS)

    Baer-Riedhart, Jennifer L.; Landy, Robert J.

    1987-01-01

    The highly integrated digital electronic control (HIDEC) program at NASA Ames Research Center, Dryden Flight Research Facility is a multiphase flight research program to quantify the benefits of promising integrated control systems. McDonnell Aircraft Company is the prime contractor, with United Technologies Pratt and Whitney Aircraft, and Lear Siegler Incorporated as major subcontractors. The NASA F-15A testbed aircraft was modified by the HIDEC program by installing a digital electronic flight control system (DEFCS) and replacing the standard F100 (Arab 3) engines with F100 engine model derivative (EMD) engines equipped with digital electronic engine controls (DEEC), and integrating the DEEC's and DEFCS. The modified aircraft provides the capability for testing many integrated control modes involving the flight controls, engine controls, and inlet controls. This paper focuses on the first two phases of the HIDEC program, which are the digital flight control system/aircraft model identification (DEFCS/AMI) phase and the adaptive engine control system (ADECS) phase.

  6. System/observer/controller identification toolbox

    NASA Technical Reports Server (NTRS)

    Juang, Jer-Nan; Horta, Lucas G.; Phan, Minh

    1992-01-01

    System Identification is the process of constructing a mathematical model from input and output data for a system under testing, and characterizing the system uncertainties and measurement noises. The mathematical model structure can take various forms depending upon the intended use. The SYSTEM/OBSERVER/CONTROLLER IDENTIFICATION TOOLBOX (SOCIT) is a collection of functions, written in MATLAB language and expressed in M-files, that implements a variety of modern system identification techniques. For an open loop system, the central features of the SOCIT are functions for identification of a system model and its corresponding forward and backward observers directly from input and output data. The system and observers are represented by a discrete model. The identified model and observers may be used for controller design of linear systems as well as identification of modal parameters such as dampings, frequencies, and mode shapes. For a closed-loop system, an observer and its corresponding controller gain directly from input and output data.

  7. Parameter identification for nonlinear aerodynamic systems

    NASA Technical Reports Server (NTRS)

    Pearson, Allan E.

    1991-01-01

    Work continues on frequency analysis for transfer function identification, both with respect to the continued development of the underlying algorithms and in the identification study of two physical systems. Some new results of a theoretical nature were recently obtained that lend further insight into the frequency domain interpretation of the research. Progress in each of those areas is summarized. Although not related to the system identification problem, some new results were obtained on the feedback stabilization of linear time lag systems.

  8. Adaptive Dialogue Systems for Assistive Living Environments

    ERIC Educational Resources Information Center

    Papangelis, Alexandros

    2013-01-01

    Adaptive Dialogue Systems (ADS) are intelligent systems, able to interact with users via multiple modalities, such as speech, gestures, facial expressions and others. Such systems are able to make conversation with their users, usually on a specific, narrow topic. Assistive Living Environments are environments where the users are by definition not…

  9. Small scale adaptive optics experiment systems engineering

    NASA Technical Reports Server (NTRS)

    Boykin, William H.

    1993-01-01

    Assessment of the current technology relating to the laser power beaming system which in full scale is called the Beam Transmission Optical System (BTOS). Evaluation of system integration efforts are being conducted by the various government agencies and industry. Concepts are being developed for prototypes of adaptive optics for a BTOS.

  10. Adaptive, full-spectrum solar energy system

    DOEpatents

    Muhs, Jeffrey D.; Earl, Dennis D.

    2003-08-05

    An adaptive full spectrum solar energy system having at least one hybrid solar concentrator, at least one hybrid luminaire, at least one hybrid photobioreactor, and a light distribution system operably connected to each hybrid solar concentrator, each hybrid luminaire, and each hybrid photobioreactor. A lighting control system operates each component.

  11. System Identification of X-33 Neural Network

    NASA Technical Reports Server (NTRS)

    Aggarwal, Shiv

    2003-01-01

    Modern flight control research has improved spacecraft survivability as its goal. To this end we need to have a failure detection system on board. In case the spacecraft is performing imperfectly, reconfiguration of control is needed. For that purpose we need to have parameter identification of spacecraft dynamics. Parameter identification of a system is called system identification. We treat the system as a black box which receives some inputs that lead to some outputs. The question is: what kind of parameters for a particular black box can correlate the observed inputs and outputs? Can these parameters help us to predict the outputs for a new given set of inputs? This is the basic problem of system identification. The X33 was supposed to have the onboard capability of evaluating the current performance and if needed to take the corrective measures to adapt to desired performance. The X33 is comprised of both rocket and aircraft vehicle design characteristics and requires, in general, analytical methods for evaluating its flight performance. Its flight consists of four phases: ascent, transition, entry and TAEM (Terminal Area Energy Management). It spends about 200 seconds in ascent phase, reaching an altitude of about 180,000 feet and a speed of about 10 to 15 Mach. During the transition phase which lasts only about 30 seconds, its altitude may increase to about 190,000 feet but its speed is reduced to about 9 Mach. At the beginning of this phase, the Main Engine is Cut Off (MECO) and the control is reconfigured with the help of aerosurfaces (four elevons, two flaps and two rudders) and reaction control system (RCS). The entry phase brings down the altitude of X33 to about 90,000 feet and its speed to about Mach 3. It spends about 250 seconds in this phase. Main engine is still cut off and the vehicle is controlled by complex maneuvers of aerosurfaces. The last phase TAEM lasts for about 450 seconds and the altitude and speed, both are reduced to zero. The

  12. Structural system identification of a composite shell

    SciTech Connect

    Red-Horse, J.R.; Carne, T.G.; James, G.H.; Witkowski, W.R.

    1991-12-31

    Structural system identification is undergoing a period of renewed interest. Probabilistic approaches to physical parameter identification in analysis finite element models make uncertainty in test results an important issue. In this paper, we investigate this issue with a simple, though in many ways representative, structural system. The results of two modal parameter identification techniques are compared and uncertainty estimates, both through bias and random errors, are quantified. The importance of the interaction between test and analysis is also highlighted. 25 refs.

  13. Structural system identification of a composite shell

    SciTech Connect

    Red-Horse, J.R.; Carne, T.G.; James, G.H.; Witkowski, W.R.

    1991-01-01

    Structural system identification is undergoing a period of renewed interest. Probabilistic approaches to physical parameter identification in analysis finite element models make uncertainty in test results an important issue. In this paper, we investigate this issue with a simple, though in many ways representative, structural system. The results of two modal parameter identification techniques are compared and uncertainty estimates, both through bias and random errors, are quantified. The importance of the interaction between test and analysis is also highlighted. 25 refs.

  14. Identification of mass disaster victims: the Swiss identification system.

    PubMed

    Mühlemann, H R; Steiner, E; Brandestini, M

    1979-01-01

    A new, simple, and reliable forensic identification system has been described. It permits the rapid and positive identification of victims of catastrophies such as airplane accidents, battles, floods, and fires. An electronic microprocessing unit directs a mechanical engraver to encode up to 13 alphanumeric characters on a small gold disk 0.25 mm thick and 2.0 mm in diameter. The identification chip is sealed in a 0.8-mm deep cavity prepared with a specially designed diamond burr in the lingual enamel of a molar tooth. The sealant is a stained composite material shown experimentally to be leakage proof, fire resistant, and readily detectable in teeth exposed to high temperatures. At the identification center the gold disk can easily be recovered and the victim positively identified without recourse to time-consuming comparison of dental records. Minimal training is required for the forensic personnel. PMID:512601

  15. Adaptive Control for Microgravity Vibration Isolation System

    NASA Technical Reports Server (NTRS)

    Yang, Bong-Jun; Calise, Anthony J.; Craig, James I.; Whorton, Mark S.

    2005-01-01

    Most active vibration isolation systems that try to a provide quiescent acceleration environment for space science experiments have utilized linear design methods. In this paper, we address adaptive control augmentation of an existing classical controller that employs a high-gain acceleration feedback together with a low-gain position feedback to center the isolated platform. The control design feature includes parametric and dynamic uncertainties because the hardware of the isolation system is built as a payload-level isolator, and the acceleration Sensor exhibits a significant bias. A neural network is incorporated to adaptively compensate for the system uncertainties, and a high-pass filter is introduced to mitigate the effect of the measurement bias. Simulations show that the adaptive control improves the performance of the existing acceleration controller and keep the level of the isolated platform deviation to that of the existing control system.

  16. Nonlinear systems identification and control via dynamic multitime scales neural networks.

    PubMed

    Fu, Zhi-Jun; Xie, Wen-Fang; Han, Xuan; Luo, Wei-Dong

    2013-11-01

    This paper deals with the adaptive nonlinear identification and trajectory tracking via dynamic multilayer neural network (NN) with different timescales. Two NN identifiers are proposed for nonlinear systems identification via dynamic NNs with different timescales including both fast and slow phenomenon. The first NN identifier uses the output signals from the actual system for the system identification. In the second NN identifier, all the output signals from nonlinear system are replaced with the state variables of the NNs. The online identification algorithms for both NN identifier parameters are proposed using Lyapunov function and singularly perturbed techniques. With the identified NN models, two indirect adaptive NN controllers for the nonlinear systems containing slow and fast dynamic processes are developed. For both developed adaptive NN controllers, the trajectory errors are analyzed and the stability of the systems is proved. Simulation results show that the controller based on the second identifier has better performance than that of the first identifier.

  17. Adaptation in the auditory system: an overview

    PubMed Central

    Pérez-González, David; Malmierca, Manuel S.

    2014-01-01

    The early stages of the auditory system need to preserve the timing information of sounds in order to extract the basic features of acoustic stimuli. At the same time, different processes of neuronal adaptation occur at several levels to further process the auditory information. For instance, auditory nerve fiber responses already experience adaptation of their firing rates, a type of response that can be found in many other auditory nuclei and may be useful for emphasizing the onset of the stimuli. However, it is at higher levels in the auditory hierarchy where more sophisticated types of neuronal processing take place. For example, stimulus-specific adaptation, where neurons show adaptation to frequent, repetitive stimuli, but maintain their responsiveness to stimuli with different physical characteristics, thus representing a distinct kind of processing that may play a role in change and deviance detection. In the auditory cortex, adaptation takes more elaborate forms, and contributes to the processing of complex sequences, auditory scene analysis and attention. Here we review the multiple types of adaptation that occur in the auditory system, which are part of the pool of resources that the neurons employ to process the auditory scene, and are critical to a proper understanding of the neuronal mechanisms that govern auditory perception. PMID:24600361

  18. Stochastic system identification in structural dynamics

    USGS Publications Warehouse

    Safak, Erdal

    1988-01-01

    Recently, new identification methods have been developed by using the concept of optimal-recursive filtering and stochastic approximation. These methods, known as stochastic identification, are based on the statistical properties of the signal and noise, and do not require the assumptions of current methods. The criterion for stochastic system identification is that the difference between the recorded output and the output from the identified system (i.e., the residual of the identification) should be equal to white noise. In this paper, first a brief review of the theory is given. Then, an application of the method is presented by using ambient vibration data from a nine-story building.

  19. Evolving Systems and Adaptive Key Component Control

    NASA Technical Reports Server (NTRS)

    Frost, Susan A.; Balas, Mark J.

    2009-01-01

    We propose a new framework called Evolving Systems to describe the self-assembly, or autonomous assembly, of actively controlled dynamical subsystems into an Evolved System with a higher purpose. An introduction to Evolving Systems and exploration of the essential topics of the control and stability properties of Evolving Systems is provided. This chapter defines a framework for Evolving Systems, develops theory and control solutions for fundamental characteristics of Evolving Systems, and provides illustrative examples of Evolving Systems and their control with adaptive key component controllers.

  20. Adaptive fuzzy system for 3-D vision

    NASA Technical Reports Server (NTRS)

    Mitra, Sunanda

    1993-01-01

    An adaptive fuzzy system using the concept of the Adaptive Resonance Theory (ART) type neural network architecture and incorporating fuzzy c-means (FCM) system equations for reclassification of cluster centers was developed. The Adaptive Fuzzy Leader Clustering (AFLC) architecture is a hybrid neural-fuzzy system which learns on-line in a stable and efficient manner. The system uses a control structure similar to that found in the Adaptive Resonance Theory (ART-1) network to identify the cluster centers initially. The initial classification of an input takes place in a two stage process; a simple competitive stage and a distance metric comparison stage. The cluster prototypes are then incrementally updated by relocating the centroid positions from Fuzzy c-Means (FCM) system equations for the centroids and the membership values. The operational characteristics of AFLC and the critical parameters involved in its operation are discussed. The performance of the AFLC algorithm is presented through application of the algorithm to the Anderson Iris data, and laser-luminescent fingerprint image data. The AFLC algorithm successfully classifies features extracted from real data, discrete or continuous, indicating the potential strength of this new clustering algorithm in analyzing complex data sets. The hybrid neuro-fuzzy AFLC algorithm will enhance analysis of a number of difficult recognition and control problems involved with Tethered Satellite Systems and on-orbit space shuttle attitude controller.

  1. System identification for robust control design

    SciTech Connect

    Dohner, J.L.

    1995-04-01

    System identification for the purpose of robust control design involves estimating a nominal model of a physical system and the uncertainty bounds of that nominal model via the use of experimentally measured input/output data. Although many algorithms have been developed to identify nominal models, little effort has been directed towards identifying uncertainty bounds. Therefore, in this document, a discussion of both nominal model identification and bounded output multiplicative uncertainty identification will be presented. This document is divided into several sections. Background information relevant to system identification and control design will be presented. A derivation of eigensystem realization type algorithms will be presented. An algorithm will be developed for calculating the maximum singular value of output multiplicative uncertainty from measured data. An application will be given involving the identification of a complex system with aliased dynamics, feedback control, and exogenous noise disturbances. And, finally, a short discussion of results will be presented.

  2. [CRISPR adaptive immunity systems of procaryotes].

    PubMed

    2012-01-01

    CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) is a newly identified prokaryotic immunity system against foreign genetic elements. In contrast to other cellular defense mechanisms (e.g. restriction-modification) CRISPR-mediated immunity is adaptive and can be programmed to protect cells against a particular bacteriophage or conjugative plasmid. In this review we describe general principles of CRISPR systems action and summarize known details of CRISPR systems from different microorganisms.

  3. Robust adaptive control of HVDC systems

    SciTech Connect

    Reeve, J.; Sultan, M. )

    1994-07-01

    The transient performance of an HVDC power system is highly dependent on the parameters of the current/voltage regulators of the converter controls. In order to better accommodate changes in system structure or dc operating conditions, this paper introduces a new adaptive control strategy. The advantages of automatic tuning for continuous fine tuning are combined with predetermined gain scheduling in order to achieve robustness for large disturbances. Examples are provided for a digitally simulated back-to-back dc system.

  4. Evaluation of Automated Yeast Identification System

    NASA Technical Reports Server (NTRS)

    McGinnis, M. R.

    1996-01-01

    One hundred and nine teleomorphic and anamorphic yeast isolates representing approximately 30 taxa were used to evaluate the accuracy of the Biolog yeast identification system. Isolates derived from nomenclatural types, environmental, and clinica isolates of known identity were tested in the Biolog system. Of the isolates tested, 81 were in the Biolog database. The system correctly identified 40, incorrectly identified 29, and was unable to identify 12. Of the 28 isolates not in the database, 18 were given names, whereas 10 were not. The Biolog yeast identification system is inadequate for the identification of yeasts originating from the environment during space program activities.

  5. Final Report - Regulatory Considerations for Adaptive Systems

    NASA Technical Reports Server (NTRS)

    Wilkinson, Chris; Lynch, Jonathan; Bharadwaj, Raj

    2013-01-01

    This report documents the findings of a preliminary research study into new approaches to the software design assurance of adaptive systems. We suggest a methodology to overcome the software validation and verification difficulties posed by the underlying assumption of non-adaptive software in the requirementsbased- testing verification methods in RTCA/DO-178B and C. An analysis of the relevant RTCA/DO-178B and C objectives is presented showing the reasons for the difficulties that arise in showing satisfaction of the objectives and suggested additional means by which they could be satisfied. We suggest that the software design assurance problem for adaptive systems is principally one of developing correct and complete high level requirements and system level constraints that define the necessary system functional and safety properties to assure the safe use of adaptive systems. We show how analytical techniques such as model based design, mathematical modeling and formal or formal-like methods can be used to both validate the high level functional and safety requirements, establish necessary constraints and provide the verification evidence for the satisfaction of requirements and constraints that supplements conventional testing. Finally the report identifies the follow-on research topics needed to implement this methodology.

  6. Dental orthopantomogram biometrics system for human identification.

    PubMed

    Singh, Sandeep; Bhargava, Darpan; Deshpande, Ashwini

    2013-07-01

    Fingerprinting is the most widely accepted method of identification of people. But in cases of disfigured, decomposed, burnt or fragmented bodies, it is of limited value. Teeth and dental restorations on the other hand are extremely resistant to destruction by fire. They retain a number of their original characteristics, which are often unique and hence offer a possibility of rather accurate and legally acceptable identification of such remains. This study was undertaken to evaluate the utility of orthopantomography for human identification and propose a coding system for orthopantomogram (OPG), which can be utilized as an identification tool in forensic sciences.

  7. Adaptive control system for gas producing wells

    SciTech Connect

    Fedor, Pashchenko; Sergey, Gulyaev; Alexander, Pashchenko

    2015-03-10

    Optimal adaptive automatic control system for gas producing wells cluster is proposed intended for solving the problem of stabilization of the output gas pressure in the cluster at conditions of changing gas flow rate and changing parameters of the wells themselves, providing the maximum high resource of hardware elements of automation.

  8. Petascale IO Using The Adaptable IO System

    SciTech Connect

    Lofstead, J.; Klasky, Scott A; Abbasi, H.

    2009-01-01

    ADIOS, the adaptable IO system, has demonstrated excellent scalability to 29,000 cores. With the introduction of the XT5 upgrades to Jaguar, new optimizations are required to successfully reach 140,000+ cores. This paper explains the techniques employed and shows the performance levels attained.

  9. Ethnolinguistic Identification and Adaptation of Repatriates in Polycultural Kazakhstan

    ERIC Educational Resources Information Center

    Bokayev, Baurzhan; Zharkynbekova, Sholpan; Nurseitova, Khalida; Bokayeva, Ainash; Akzhigitova, Assel; Nurgalieva, Saniya

    2012-01-01

    The issues of social, cultural, and language adjustment and the integration of repatriates into the Kazakhstani society are crucial factors in maintaining a stable society. The complicated process of self-identification of ethnic Kazakhs is a major aspect of their sociolinguistic "penetration" into Kazakh society. In this work we consider the…

  10. On neural networks in identification and control of dynamic systems

    NASA Technical Reports Server (NTRS)

    Phan, Minh; Juang, Jer-Nan; Hyland, David C.

    1993-01-01

    This paper presents a discussion of the applicability of neural networks in the identification and control of dynamic systems. Emphasis is placed on the understanding of how the neural networks handle linear systems and how the new approach is related to conventional system identification and control methods. Extensions of the approach to nonlinear systems are then made. The paper explains the fundamental concepts of neural networks in their simplest terms. Among the topics discussed are feed forward and recurrent networks in relation to the standard state-space and observer models, linear and nonlinear auto-regressive models, linear, predictors, one-step ahead control, and model reference adaptive control for linear and nonlinear systems. Numerical examples are presented to illustrate the application of these important concepts.

  11. Adaptive output feedback control of flexible systems

    NASA Astrophysics Data System (ADS)

    Yang, Bong-Jun

    Neural network-based adaptive output feedback approaches that augment a linear control design are described in this thesis, and emphasis is placed on their real-time implementation with flexible systems. Two different control architectures that are robust to parametric uncertainties and unmodelled dynamics are presented. The unmodelled effects can consist of minimum phase internal dynamics of the system together with external disturbance process. Within this context, adaptive compensation for external disturbances is addressed. In the first approach, internal model-following control, adaptive elements are designed using feedback inversion. The effect of an actuator limit is treated using control hedging, and the effect of other actuation nonlinearities, such as dead zone and backlash, is mitigated by a disturbance observer-based control design. The effectiveness of the approach is illustrated through simulation and experimental testing with a three-disk torsional system, which is subjected to control voltage limit and stiction. While the internal model-following control is limited to minimum phase systems, the second approach, external model-following control, does not involve feedback linearization and can be applied to non-minimum phase systems. The unstable zero dynamics are assumed to have been modelled in the design of the existing linear controller. The laboratory tests for this method include a three-disk torsional pendulum, an inverted pendulum, and a flexible-base robot manipulator. The external model-following control architecture is further extended in three ways. The first extension is an approach for control of multivariable nonlinear systems. The second extension is a decentralized adaptive control approach for large-scale interconnected systems. The third extension is to make use of an adaptive observer to augment a linear observer-based controller. In this extension, augmenting terms for the adaptive observer can be used to achieve adaptation in

  12. Learning and adaptation in fuzzy neural systems

    NASA Astrophysics Data System (ADS)

    Gupta, Madan M.

    1992-03-01

    In recent years, an increasing number of researchers have become involved in the subject of fuzzy neural networks in the hope of combining the reasoning strength of fuzzy logic and the learning and adaptation power of neural networks. This provides a more powerful tool for fuzzy information processing and for exploring the functioning of human brains. In this paper, an attempt has been made to establish some basic models for fuzzy neurons. First, several possible fuzzy neuron models are proposed. Second, synaptic and somatic learning and adaptation mechanisms are proposed. Finally, the possibility of applying nonfuzzy neural networks approaches to fuzzy systems is also described.

  13. Adaptive control design for hysteretic smart systems

    NASA Astrophysics Data System (ADS)

    McMahan, Jerry A.; Smith, Ralph C.

    2011-04-01

    Ferroelectric and ferromagnetic actuators are being considered for a range of industrial, aerospace, aeronautic and biomedical applications due to their unique transduction capabilities. However, they also exhibit hysteretic and nonlinear behavior that must be accommodated in models and control designs. If uncompensated, these effects can yield reduced system performance and, in the worst case, can produce unpredictable behavior of the control system. In this paper, we address the development of adaptive control designs for hysteretic systems. We review an MRAC-like adaptive control algorithm used to track a reference trajectory while computing online estimates for certain model parameters. This method is incorporated in a composite control algorithm to improve the tracking capabilities of the system. Issues arising in the implementation of these algorithms are addressed, and a numerical example is presented, comparing the results of each method.

  14. Adaptable Transponder for Multiple Telemetry Systems

    NASA Technical Reports Server (NTRS)

    Sims, William Herbert, III (Inventor); Varnavas, Kosta A. (Inventor)

    2014-01-01

    The present invention is a stackable telemetry circuit board for use in telemetry systems for satellites and other purposes. The present invention incorporates previously-qualified interchangeable circuit boards, or "decks," that perform functions such as power, signal receiving and transmission, and processing. Each deck is adapted to serve a range of telemetry applications. This provides flexibility in the construction of the stackable telemetry circuit board and significantly reduces the cost and time necessary to develop a telemetry system.

  15. An adaptive P300-based control system

    NASA Astrophysics Data System (ADS)

    Jin, Jing; Allison, Brendan Z.; Sellers, Eric W.; Brunner, Clemens; Horki, Petar; Wang, Xingyu; Neuper, Christa

    2011-06-01

    An adaptive P300 brain-computer interface (BCI) using a 12 × 7 matrix explored new paradigms to improve bit rate and accuracy. During online use, the system adaptively selects the number of flashes to average. Five different flash patterns were tested. The 19-flash paradigm represents the typical row/column presentation (i.e. 12 columns and 7 rows). The 9- and 14-flash A and B paradigms present all items of the 12 × 7 matrix three times using either 9 or 14 flashes (instead of 19), decreasing the amount of time to present stimuli. Compared to 9-flash A, 9-flash B decreased the likelihood that neighboring items would flash when the target was not flashing, thereby reducing the interference from items adjacent to targets. 14-flash A also reduced the adjacent item interference and 14-flash B additionally eliminated successive (double) flashes of the same item. Results showed that the accuracy and bit rate of the adaptive system were higher than those of the non-adaptive system. In addition, 9- and 14-flash B produced significantly higher performance than their respective A conditions. The results also show the trend that the 14-flash B paradigm was better than the 19-flash pattern for naive users.

  16. Adaptive Learning Resources Sequencing in Educational Hypermedia Systems

    ERIC Educational Resources Information Center

    Karampiperis, Pythagoras; Sampson, Demetrios

    2005-01-01

    Adaptive learning resources selection and sequencing is recognized as among the most interesting research questions in adaptive educational hypermedia systems (AEHS). In order to adaptively select and sequence learning resources in AEHS, the definition of adaptation rules contained in the Adaptation Model, is required. Although, some efforts have…

  17. Adaptive functional systems: Learning with chaos

    NASA Astrophysics Data System (ADS)

    Komarov, M. A.; Osipov, G. V.; Burtsev, M. S.

    2010-12-01

    We propose a new model of adaptive behavior that combines a winnerless competition principle and chaos to learn new functional systems. The model consists of a complex network of nonlinear dynamical elements producing sequences of goal-directed actions. Each element describes dynamics and activity of the functional system which is supposed to be a distributed set of interacting physiological elements such as nerve or muscle that cooperates to obtain certain goal at the level of the whole organism. During "normal" behavior, the dynamics of the system follows heteroclinic channels, but in the novel situation chaotic search is activated and a new channel leading to the target state is gradually created simulating the process of learning. The model was tested in single and multigoal environments and had demonstrated a good potential for generation of new adaptations.

  18. Adaptive convex combination approach for the identification of improper quaternion processes.

    PubMed

    Ujang, Bukhari Che; Jahanchahi, Cyrus; Took, Clive Cheong; Mandic, Danilo P

    2014-01-01

    Data-adaptive optimal modeling and identification of real-world vector sensor data is provided by combining the fractional tap-length (FT) approach with model order selection in the quaternion domain. To account rigorously for the generality of such processes, both second-order circular (proper) and noncircular (improper), the proposed approach in this paper combines the FT length optimization with both the strictly linear quaternion least mean square (QLMS) and widely linear QLMS (WL-QLMS). A collaborative approach based on QLMS and WL-QLMS is shown to both identify the type of processes (proper or improper) and to track their optimal parameters in real time. Analysis shows that monitoring the evolution of the convex mixing parameter within the collaborative approach allows us to track the improperness in real time. Further insight into the properties of those algorithms is provided by establishing a relationship between the steady-state error and optimal model order. The approach is supported by simulations on model order selection and identification of both strictly linear and widely linear quaternion-valued systems, such as those routinely used in renewable energy (wind) and human-centered computing (biomechanics). PMID:24806652

  19. Adaptive Embedded Digital System for Plasma Diagnostics

    NASA Astrophysics Data System (ADS)

    González, Angel; Rodríguez, Othoniel; Mangual, Osvaldo; Ponce, Eduardo; Vélez, Xavier

    2014-05-01

    An Adaptive Embedded Digital System to perform plasma diagnostics using electrostatic probes was developed at the Plasma Engineering Laboratory at Polytechnic University of Puerto Rico. The system will replace the existing instrumentation at the Laboratory, using reconfigurable hardware to minimize the equipment and software needed to perform diagnostics. The adaptability of the design resides on the possibility of replacing the computational algorithm on the fly, allowing to use the same hardware for different probes. The system was prototyped using Very High Speed Integrated Circuits Hardware Description Language (VHDL) into an Field Programmable Gate Array (FPGA) board. The design of the Embedded Digital System includes a Zero Phase Digital Filter, a Derivative Unit, and a Computational Unit designed using the VHDL-2008 Support Library. The prototype is able to compute the Plasma Electron Temperature and Density from a Single Langmuir probe. The system was tested using real data previously acquired from a single Langmuir probe. The plasma parameters obtained from the embedded system were compared with results computed using matlab yielding excellent matching. The new embedded system operates on 4096 samples versus 500 on the previous system, and completes its computations in 26 milliseconds compared with about 15 seconds on the previous system.

  20. Phase coherence adaptive processor for automatic signal detection and identification

    NASA Astrophysics Data System (ADS)

    Wagstaff, Ronald A.

    2006-05-01

    A continuously adapting acoustic signal processor with an automatic detection/decision aid is presented. Its purpose is to preserve the signals of tactical interest, and filter out other signals and noise. It utilizes single sensor or beamformed spectral data and transforms the signal and noise phase angles into "aligned phase angles" (APA). The APA increase the phase temporal coherence of signals and leave the noise incoherent. Coherence thresholds are set, which are representative of the type of source "threat vehicle" and the geographic area or volume in which it is operating. These thresholds separate signals, based on the "quality" of their APA coherence. An example is presented in which signals from a submerged source in the ocean are preserved, while clutter signals from ships and noise are entirely eliminated. Furthermore, the "signals of interest" were identified by the processor's automatic detection aid. Similar performance is expected for air and ground vehicles. The processor's equations are formulated in such a manner that they can be tuned to eliminate noise and exploit signal, based on the "quality" of their APA temporal coherence. The mathematical formulation for this processor is presented, including the method by which the processor continuously self-adapts. Results show nearly complete elimination of noise, with only the selected category of signals remaining, and accompanying enhancements in spectral and spatial resolution. In most cases, the concept of signal-to-noise ratio looses significance, and "adaptive automated /decision aid" is more relevant.

  1. Adaptive Optics Imaging of Solar System Objects

    NASA Technical Reports Server (NTRS)

    Roddier, Francois; Owen, Toby

    1997-01-01

    Most solar system objects have never been observed at wavelengths longer than the R band with an angular resolution better than 1 sec. The Hubble Space Telescope itself has only recently been equipped to observe in the infrared. However, because of its small diameter, the angular resolution is lower than that one can now achieved from the ground with adaptive optics, and time allocated to planetary science is limited. We have been using adaptive optics (AO) on a 4-m class telescope to obtain 0.1 sec resolution images solar system objects at far red and near infrared wavelengths (0.7-2.5 micron) which best discriminate their spectral signatures. Our efforts has been put into areas of research for which high angular resolution is essential, such as the mapping of Titan and of large asteroids, the dynamics and composition of Neptune stratospheric clouds, the infrared photometry of Pluto, Charon, and close satellites previously undetected from the ground.

  2. Adaptive Optics Imaging of Solar System Objects

    NASA Technical Reports Server (NTRS)

    Roddier, Francois; Owen, Toby

    1999-01-01

    Most solar system objects have never been observed at wavelengths longer than the R band with an angular resolution better than 1". The Hubble Space Telescope itself has only recently been equipped to observe in the infrared. However, because of its small diameter, the angular resolution is lower than that one can now achieved from the ground with adaptive optics, and time allocated to planetary science is limited. We have successfully used adaptive optics on a 4-m class telescope to obtain 0.1" resolution images of solar system objects in the far red and near infrared (0.7-2.5 microns), aE wavelengths which best discl"lmlnate their spectral signatures. Our efforts have been put into areas of research for which high angular resolution is essential.

  3. Adaptable radiation monitoring system and method

    DOEpatents

    Archer, Daniel E.; Beauchamp, Brock R.; Mauger, G. Joseph; Nelson, Karl E.; Mercer, Michael B.; Pletcher, David C.; Riot, Vincent J.; Schek, James L.; Knapp, David A.

    2006-06-20

    A portable radioactive-material detection system capable of detecting radioactive sources moving at high speeds. The system has at least one radiation detector capable of detecting gamma-radiation and coupled to an MCA capable of collecting spectral data in very small time bins of less than about 150 msec. A computer processor is connected to the MCA for determining from the spectral data if a triggering event has occurred. Spectral data is stored on a data storage device, and a power source supplies power to the detection system. Various configurations of the detection system may be adaptably arranged for various radiation detection scenarios. In a preferred embodiment, the computer processor operates as a server which receives spectral data from other networked detection systems, and communicates the collected data to a central data reporting system.

  4. Nuclear Materials Identification System Operational Manual

    SciTech Connect

    Chiang, L.G.

    2001-04-10

    This report describes the operation and setup of the Nuclear Materials Identification System (NMIS) with a {sup 252}Cf neutron source at the Oak Ridge Y-12 Plant. The components of the system are described with a description of the setup of the system along with an overview of the NMIS measurements for scanning, calibration, and confirmation of inventory items.

  5. Modeling, system identification, and control of ASTREX

    NASA Technical Reports Server (NTRS)

    Abhyankar, Nandu S.; Ramakrishnan, J.; Byun, K. W.; Das, A.; Cossey, Derek F.; Berg, J.

    1993-01-01

    The modeling, system identification and controller design aspects of the ASTREX precision space structure are presented in this work. Modeling of ASTREX is performed using NASTRAN, TREETOPS and I-DEAS. The models generated range from simple linear time-invariant models to nonlinear models used for large angle simulations. Identification in both the time and frequency domains are presented. The experimental set up and the results from the identification experiments are included. Finally, controller design for ASTREX is presented. Simulation results using this optimal controller demonstrate the controller performance. Finally the future directions and plans for the facility are addressed.

  6. Multi-level RF identification system

    DOEpatents

    Steele, Kerry D.; Anderson, Gordon A.; Gilbert, Ronald W.

    2004-07-20

    A radio frequency identification system having a radio frequency transceiver for generating a continuous wave RF interrogation signal that impinges upon an RF identification tag. An oscillation circuit in the RF identification tag modulates the interrogation signal with a subcarrier of a predetermined frequency and modulates the frequency-modulated signal back to the transmitting interrogator. The interrogator recovers and analyzes the subcarrier signal and determines its frequency. The interrogator generates an output indicative of the frequency of the subcarrier frequency, thereby identifying the responding RFID tag as one of a "class" of RFID tags configured to respond with a subcarrier signal of a predetermined frequency.

  7. Modeling, system identification, and control of ASTREX

    NASA Astrophysics Data System (ADS)

    Abhyankar, Nandu S.; Ramakrishnan, J.; Byun, K. W.; Das, A.; Cossey, Derek F.; Berg, J.

    1993-02-01

    The modeling, system identification and controller design aspects of the ASTREX precision space structure are presented in this work. Modeling of ASTREX is performed using NASTRAN, TREETOPS and I-DEAS. The models generated range from simple linear time-invariant models to nonlinear models used for large angle simulations. Identification in both the time and frequency domains are presented. The experimental set up and the results from the identification experiments are included. Finally, controller design for ASTREX is presented. Simulation results using this optimal controller demonstrate the controller performance. Finally the future directions and plans for the facility are addressed.

  8. Gaia as a complex adaptive system.

    PubMed

    Lenton, Timothy M; van Oijen, Marcel

    2002-05-29

    We define the Gaia system of life and its environment on Earth, review the status of the Gaia theory, introduce potentially relevant concepts from complexity theory, then try to apply them to Gaia. We consider whether Gaia is a complex adaptive system (CAS) in terms of its behaviour and suggest that the system is self-organizing but does not reside in a critical state. Gaia has supported abundant life for most of the last 3.8 Gyr. Large perturbations have occasionally suppressed life but the system has always recovered without losing the capacity for large-scale free energy capture and recycling of essential elements. To illustrate how complexity theory can help us understand the emergence of planetary-scale order, we present a simple cellular automata (CA) model of the imaginary planet Daisyworld. This exhibits emergent self-regulation as a consequence of feedback coupling between life and its environment. Local spatial interaction, which was absent from the original model, can destabilize the system by generating bifurcation regimes. Variation and natural selection tend to remove this instability. With mutation in the model system, it exhibits self-organizing adaptive behaviour in its response to forcing. We close by suggesting how artificial life ('Alife') techniques may enable more comprehensive feasibility tests of Gaia. PMID:12079529

  9. Gaia as a complex adaptive system.

    PubMed

    Lenton, Timothy M; van Oijen, Marcel

    2002-05-29

    We define the Gaia system of life and its environment on Earth, review the status of the Gaia theory, introduce potentially relevant concepts from complexity theory, then try to apply them to Gaia. We consider whether Gaia is a complex adaptive system (CAS) in terms of its behaviour and suggest that the system is self-organizing but does not reside in a critical state. Gaia has supported abundant life for most of the last 3.8 Gyr. Large perturbations have occasionally suppressed life but the system has always recovered without losing the capacity for large-scale free energy capture and recycling of essential elements. To illustrate how complexity theory can help us understand the emergence of planetary-scale order, we present a simple cellular automata (CA) model of the imaginary planet Daisyworld. This exhibits emergent self-regulation as a consequence of feedback coupling between life and its environment. Local spatial interaction, which was absent from the original model, can destabilize the system by generating bifurcation regimes. Variation and natural selection tend to remove this instability. With mutation in the model system, it exhibits self-organizing adaptive behaviour in its response to forcing. We close by suggesting how artificial life ('Alife') techniques may enable more comprehensive feasibility tests of Gaia.

  10. Gaia as a complex adaptive system.

    PubMed Central

    Lenton, Timothy M; van Oijen, Marcel

    2002-01-01

    We define the Gaia system of life and its environment on Earth, review the status of the Gaia theory, introduce potentially relevant concepts from complexity theory, then try to apply them to Gaia. We consider whether Gaia is a complex adaptive system (CAS) in terms of its behaviour and suggest that the system is self-organizing but does not reside in a critical state. Gaia has supported abundant life for most of the last 3.8 Gyr. Large perturbations have occasionally suppressed life but the system has always recovered without losing the capacity for large-scale free energy capture and recycling of essential elements. To illustrate how complexity theory can help us understand the emergence of planetary-scale order, we present a simple cellular automata (CA) model of the imaginary planet Daisyworld. This exhibits emergent self-regulation as a consequence of feedback coupling between life and its environment. Local spatial interaction, which was absent from the original model, can destabilize the system by generating bifurcation regimes. Variation and natural selection tend to remove this instability. With mutation in the model system, it exhibits self-organizing adaptive behaviour in its response to forcing. We close by suggesting how artificial life ('Alife') techniques may enable more comprehensive feasibility tests of Gaia. PMID:12079529

  11. Systems integration of innate and adaptive immunity.

    PubMed

    Zak, Daniel E; Aderem, Alan

    2015-09-29

    The pathogens causing AIDS, malaria, and tuberculosis have proven too complex to be overcome by classical approaches to vaccination. The complexities of human immunology and pathogen-induced modulation of the immune system mandate new approaches to vaccine discovery and design. A new field, systems vaccinology, weds holistic analysis of innate and adaptive immunity within a quantitative framework to enable rational design of new vaccines that elicit tailored protective immune responses. A key step in the approach is to discover relationships between the earliest innate inflammatory responses to vaccination and the subsequent vaccine-induced adaptive immune responses and efficacy. Analysis of these responses in clinical studies is complicated by the inaccessibility of relevant tissue compartments (such as the lymph node), necessitating reliance upon peripheral blood responses as surrogates. Blood transcriptomes, although indirect to vaccine mechanisms, have proven very informative in systems vaccinology studies. The approach is most powerful when innate and adaptive immune responses are integrated with vaccine efficacy, which is possible for malaria with the advent of a robust human challenge model. This is more difficult for AIDS and tuberculosis, given that human challenge models are lacking and efficacy observed in clinical trials has been low or highly variable. This challenge can be met by appropriate clinical trial design for partially efficacious vaccines and by analysis of natural infection cohorts. Ultimately, systems vaccinology is an iterative approach in which mechanistic hypotheses-derived from analysis of clinical studies-are evaluated in model systems, and then used to guide the development of new vaccine strategies. In this review, we will illustrate the above facets of the systems vaccinology approach with case studies.

  12. On Markov parameters in system identification

    NASA Technical Reports Server (NTRS)

    Phan, Minh; Juang, Jer-Nan; Longman, Richard W.

    1991-01-01

    A detailed discussion of Markov parameters in system identification is given. Different forms of input-output representation of linear discrete-time systems are reviewed and discussed. Interpretation of sampled response data as Markov parameters is presented. Relations between the state-space model and particular linear difference models via the Markov parameters are formulated. A generalization of Markov parameters to observer and Kalman filter Markov parameters for system identification is explained. These extended Markov parameters play an important role in providing not only a state-space realization, but also an observer/Kalman filter for the system of interest.

  13. Investigation of the Multiple Method Adaptive Control (MMAC) method for flight control systems

    NASA Technical Reports Server (NTRS)

    Athans, M.; Baram, Y.; Castanon, D.; Dunn, K. P.; Green, C. S.; Lee, W. H.; Sandell, N. R., Jr.; Willsky, A. S.

    1979-01-01

    The stochastic adaptive control of the NASA F-8C digital-fly-by-wire aircraft using the multiple model adaptive control (MMAC) method is presented. The selection of the performance criteria for the lateral and the longitudinal dynamics, the design of the Kalman filters for different operating conditions, the identification algorithm associated with the MMAC method, the control system design, and simulation results obtained using the real time simulator of the F-8 aircraft at the NASA Langley Research Center are discussed.

  14. Complex Adaptive Systems of Systems (CASOS) engineering environment.

    SciTech Connect

    Detry, Richard Joseph; Linebarger, John Michael; Finley, Patrick D.; Maffitt, S. Louise; Glass, Robert John, Jr.; Beyeler, Walter Eugene; Ames, Arlo Leroy

    2012-02-01

    Complex Adaptive Systems of Systems, or CASoS, are vastly complex physical-socio-technical systems which we must understand to design a secure future for the nation. The Phoenix initiative implements CASoS Engineering principles combining the bottom up Complex Systems and Complex Adaptive Systems view with the top down Systems Engineering and System-of-Systems view. CASoS Engineering theory and practice must be conducted together to develop a discipline that is grounded in reality, extends our understanding of how CASoS behave and allows us to better control the outcomes. The pull of applications (real world problems) is critical to this effort, as is the articulation of a CASoS Engineering Framework that grounds an engineering approach in the theory of complex adaptive systems of systems. Successful application of the CASoS Engineering Framework requires modeling, simulation and analysis (MS and A) capabilities and the cultivation of a CASoS Engineering Community of Practice through knowledge sharing and facilitation. The CASoS Engineering Environment, itself a complex adaptive system of systems, constitutes the two platforms that provide these capabilities.

  15. Social networks as embedded complex adaptive systems.

    PubMed

    Benham-Hutchins, Marge; Clancy, Thomas R

    2010-09-01

    As systems evolve over time, their natural tendency is to become increasingly more complex. Studies in the field of complex systems have generated new perspectives on management in social organizations such as hospitals. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. This is the 15th in a series of articles applying complex systems science to the traditional management concepts of planning, organizing, directing, coordinating, and controlling. In this article, the authors discuss healthcare social networks as a hierarchy of embedded complex adaptive systems. The authors further examine the use of social network analysis tools as a means to understand complex communication patterns and reduce medical errors.

  16. Spectators' identification with French sports teams: a French adaptation of the sport spectator identification scale.

    PubMed

    Bernache-Assollant, Iouri; Bouchet, Patrick; Lacassagne, Marie-Françoise

    2007-02-01

    Due to the works of Wann and colleagues, spectators' identification with teams has taken on a central role in the study of sports spectators' thought and behavior. However, no research in this area has measured identification with sports teams in the French context. Two studies attempted to develop a valid and reliable French version of the Sport Spectator Identification Scale (SSIS) developed by Wann and Branscombe in 1993 to measure team identification. In Study 1, 200 physical education students completed a French translation of the SSIS and several questions concerning their involvement, investment, and evaluation of the team's future performance. Results showed that the French translation of the SSIS is a reliable and one-dimensional instrument: strong relationships were found between identification with professional French teams and these variables. In Study 2, 143 physical education students completed the SSIS with a National sport team as the target team. Results confirmed the psychometric properties of the scale and indicated that persons who strongly identify with the National soccer team reported more involvement with the team and were more optimistic about future performances than persons low in identification.

  17. Performance assessment of MEMS adaptive optics in tactical airborne systems

    NASA Astrophysics Data System (ADS)

    Tyson, Robert K.

    1999-09-01

    Tactical airborne electro-optical systems are severely constrained by weight, volume, power, and cost. Micro- electrical-mechanical adaptive optics provide a solution that addresses the engineering realities without compromising spatial and temporal compensation requirements. Through modeling and analysis, we determined that substantial benefits could be gained for laser designators, ladar, countermeasures, and missile seekers. The developments potential exists for improving seeker imagery resolution 20 percent, extending countermeasures keep-out range by a factor of 5, doubling the range for ladar detection and identification, and compensating for supersonic and hypersonic aircraft boundary layers. Innovative concepts are required for atmospheric pat hand boundary layer compensation. We have developed design that perform these tasks using high speed scene-based wavefront sensing, IR aerosol laser guide stars, and extended-object wavefront beacons. We have developed a number of adaptive optics system configurations that met the spatial resolution requirements and we have determined that sensing and signal processing requirements can be met. With the help of micromachined deformable mirrors and sensor, we will be able to integrate the systems into existing airborne pods and missiles as well as next generation electro-optical systems.

  18. Adapting classical Systems Engineering to Department of Energy (DOE) needs

    SciTech Connect

    1996-07-01

    Rather than discuss Systems Engineering (SE) as applied by aerospace contractors to military programs, this document provides an adapted model well suited for use by DOE and represents 18 months of applying SE principles to the challenges faced by INEL. The real-life examples are drawn from INEL`s ongoing effort to integrate activities across the entire spectrum of within its Environmental Management program. Since the traditional SE process, with its initial focus on requirements identification and analysis, must be modified to provide tangible results in the short term, the adapted SE model starts with the external driver of ``reducing costs without increasing risks`` and performs an initial integration effort to identify high-potential, cost-saving opportunities. Elements from traditional alternatives development and analysis stages are used; then the adapted model cycles back to include more traditional requirements analysis activities. These cycles continue in an iterative manner, adding rigor and detail at each successive iteration, throughout the life-cycle of a program or project. Detailed lessons learned are included.

  19. System identification of the Arabidopsis plant circadian system

    NASA Astrophysics Data System (ADS)

    Foo, Mathias; Somers, David E.; Kim, Pan-Jun

    2015-02-01

    The circadian system generates an endogenous oscillatory rhythm that governs the daily activities of organisms in nature. It offers adaptive advantages to organisms through a coordination of their biological functions with the optimal time of day. In this paper, a model of the circadian system in the plant Arabidopsis (species thaliana) is built by using system identification techniques. Prior knowledge about the physical interactions of the genes and the proteins in the plant circadian system is incorporated in the model building exercise. The model is built by using primarily experimentally-verified direct interactions between the genes and the proteins with the available data on mRNA and protein abundances from the circadian system. Our analysis reveals a great performance of the model in predicting the dynamics of the plant circadian system through the effect of diverse internal and external perturbations (gene knockouts and day-length changes). Furthermore, we found that the circadian oscillatory rhythm is robust and does not vary much with the biochemical parameters except those of a light-sensitive protein P and a transcription factor TOC1. In other words, the circadian rhythmic profile is largely a consequence of the network's architecture rather than its particular parameters. Our work suggests that the current experimental knowledge of the gene-to-protein interactions in the plant Arabidopsis, without considering any additional hypothetical interactions, seems to suffice for system-level modeling of the circadian system of this plant and to present an exemplary platform for the control of network dynamics in complex living organisms.

  20. Laser/rf personnel identification system

    NASA Astrophysics Data System (ADS)

    Zari, Michael C.; Ward, Reeder N.; Hess, David A.; Anderson, Christopher S.

    1995-05-01

    This paper documents the design of a Laser/RF Personnel Identification System developed for the US Army Communications and Electronics Command (CECOM) for soldier identification. The system has dual use applications, including law enforcement officer protection, and includes a laser interrogation unit with a programmable activation code. The interrogation unit is very directive for low probability of intercept (LPI), which is of interest during covert operations. A responder unit, worn by the law enforcement personnel or soldier, transmits an LPI radio frequency (RF) response only after receiving the proper interrogation code. The basic subsystems for the identification system are a laser interrogation unit, an RF responder unit, and a programming/synchronization unit. In this paper, the operating principles for the subsystems are reviewed and design issues are discussed. In addition to the design performed for CECOM, a breadboard system was developed to validate the concept. Hardware implementation is reviewed and field testing of the breadboard is presented.

  1. Adaptive Identification and Characterization of Polar Ionization Patches

    NASA Technical Reports Server (NTRS)

    Coley, W. R.; Heelis, R. A.

    1995-01-01

    Dynamics Explorer 2 (DE 2) spacecraft data are used to detect and characterize polar cap 'ionization patches' loosely defined as large-scale (greater than 100 km) regions where the F region plasma density is significantly enhanced (approx greater than 100%) above the background level. These patches are generally believed to develop in or equatorward of the dayside cusp region and then drift in an antisunward direction over the polar cap. We have developed a flexible algorithm for the identification and characterization of these structures, as a function of scale-size and density enhancement, using data from the retarding potential analyzer, the ion drift meter, and the langmuir probe on board the DE 2 satellite. This algorithm was used to study the structure and evolution of ionization patches as they cross the polar cap. The results indicate that in the altitude region from 240 to 950 km ion density enhancements greater than a factor of 3 above the background level are relatively rare. Further, the ionization patches show a preferred horizontal scale size of 300-400 km. There exists a clear seasonal and universal time dependence to the occurrence frequency of patches with a northern hemisphere maximum centered on the winter solstice and the 1200-2000 UT interval.

  2. DKIST Adaptive Optics System: Simulation Results

    NASA Astrophysics Data System (ADS)

    Marino, Jose; Schmidt, Dirk

    2016-05-01

    The 4 m class Daniel K. Inouye Solar Telescope (DKIST), currently under construction, will be equipped with an ultra high order solar adaptive optics (AO) system. The requirements and capabilities of such a solar AO system are beyond those of any other solar AO system currently in operation. We must rely on solar AO simulations to estimate and quantify its performance.We present performance estimation results of the DKIST AO system obtained with a new solar AO simulation tool. This simulation tool is a flexible and fast end-to-end solar AO simulator which produces accurate solar AO simulations while taking advantage of current multi-core computer technology. It relies on full imaging simulations of the extended field Shack-Hartmann wavefront sensor (WFS), which directly includes important secondary effects such as field dependent distortions and varying contrast of the WFS sub-aperture images.

  3. Adaptable data management for systems biology investigations

    PubMed Central

    Boyle, John; Rovira, Hector; Cavnor, Chris; Burdick, David; Killcoyne, Sarah; Shmulevich, Ilya

    2009-01-01

    Background Within research each experiment is different, the focus changes and the data is generated from a continually evolving barrage of technologies. There is a continual introduction of new techniques whose usage ranges from in-house protocols through to high-throughput instrumentation. To support these requirements data management systems are needed that can be rapidly built and readily adapted for new usage. Results The adaptable data management system discussed is designed to support the seamless mining and analysis of biological experiment data that is commonly used in systems biology (e.g. ChIP-chip, gene expression, proteomics, imaging, flow cytometry). We use different content graphs to represent different views upon the data. These views are designed for different roles: equipment specific views are used to gather instrumentation information; data processing oriented views are provided to enable the rapid development of analysis applications; and research project specific views are used to organize information for individual research experiments. This management system allows for both the rapid introduction of new types of information and the evolution of the knowledge it represents. Conclusion Data management is an important aspect of any research enterprise. It is the foundation on which most applications are built, and must be easily extended to serve new functionality for new scientific areas. We have found that adopting a three-tier architecture for data management, built around distributed standardized content repositories, allows us to rapidly develop new applications to support a diverse user community. PMID:19265554

  4. Adaptive PVDF piezoelectric deformable mirror system.

    PubMed

    Sato, T; Ishida, H; Ikeda, O

    1980-05-01

    An adaptive mirror system whose surface deforms smoothly according to the desired curve has been made of polyvinylidene fluoride (PVDF) piezoelectric film and laminar glass plate. One surface of the glass plate was evaporated with silver, and this side was used as the mirror surface. A PVDF film, whose shape was determined by the deformation curve, was pasted tightly on the other surface. The mirror deforms smoothly along this curve with the application of a single voltage to the film. Holographic filter and feedback were lso considered to improve the static and dynamic characteristics. Typically, deformation along ax(2)+bx(3) was obtained. PMID:20221054

  5. Robust identification of local adaptation from allele frequencies.

    PubMed

    Günther, Torsten; Coop, Graham

    2013-09-01

    Comparing allele frequencies among populations that differ in environment has long been a tool for detecting loci involved in local adaptation. However, such analyses are complicated by an imperfect knowledge of population allele frequencies and neutral correlations of allele frequencies among populations due to shared population history and gene flow. Here we develop a set of methods to robustly test for unusual allele frequency patterns and correlations between environmental variables and allele frequencies while accounting for these complications based on a Bayesian model previously implemented in the software Bayenv. Using this model, we calculate a set of "standardized allele frequencies" that allows investigators to apply tests of their choice to multiple populations while accounting for sampling and covariance due to population history. We illustrate this first by showing that these standardized frequencies can be used to detect nonparametric correlations with environmental variables; these correlations are also less prone to spurious results due to outlier populations. We then demonstrate how these standardized allele frequencies can be used to construct a test to detect SNPs that deviate strongly from neutral population structure. This test is conceptually related to FST and is shown to be more powerful, as we account for population history. We also extend the model to next-generation sequencing of population pools-a cost-efficient way to estimate population allele frequencies, but one that introduces an additional level of sampling noise. The utility of these methods is demonstrated in simulations and by reanalyzing human SNP data from the Human Genome Diversity Panel populations and pooled next-generation sequencing data from Atlantic herring. An implementation of our method is available from http://gcbias.org. PMID:23821598

  6. Robust Identification of Local Adaptation from Allele Frequencies

    PubMed Central

    Günther, Torsten; Coop, Graham

    2013-01-01

    Comparing allele frequencies among populations that differ in environment has long been a tool for detecting loci involved in local adaptation. However, such analyses are complicated by an imperfect knowledge of population allele frequencies and neutral correlations of allele frequencies among populations due to shared population history and gene flow. Here we develop a set of methods to robustly test for unusual allele frequency patterns and correlations between environmental variables and allele frequencies while accounting for these complications based on a Bayesian model previously implemented in the software Bayenv. Using this model, we calculate a set of “standardized allele frequencies” that allows investigators to apply tests of their choice to multiple populations while accounting for sampling and covariance due to population history. We illustrate this first by showing that these standardized frequencies can be used to detect nonparametric correlations with environmental variables; these correlations are also less prone to spurious results due to outlier populations. We then demonstrate how these standardized allele frequencies can be used to construct a test to detect SNPs that deviate strongly from neutral population structure. This test is conceptually related to FST and is shown to be more powerful, as we account for population history. We also extend the model to next-generation sequencing of population pools—a cost-efficient way to estimate population allele frequencies, but one that introduces an additional level of sampling noise. The utility of these methods is demonstrated in simulations and by reanalyzing human SNP data from the Human Genome Diversity Panel populations and pooled next-generation sequencing data from Atlantic herring. An implementation of our method is available from http://gcbias.org. PMID:23821598

  7. Finite-time master-slave synchronization and parameter identification for uncertain Lurie systems.

    PubMed

    Wang, Tianbo; Zhao, Shouwei; Zhou, Wuneng; Yu, Weiqin

    2014-07-01

    This paper investigates the finite-time master-slave synchronization and parameter identification problem for uncertain Lurie systems based on the finite-time stability theory and the adaptive control method. The finite-time master-slave synchronization means that the state of a slave system follows with that of a master system in finite time, which is more reasonable than the asymptotical synchronization in applications. The uncertainties include the unknown parameters and noise disturbances. An adaptive controller and update laws which ensures the synchronization and parameter identification to be realized in finite time are constructed. Finally, two numerical examples are given to show the effectiveness of the proposed method.

  8. Adaptive generalized combination complex synchronization of uncertain real and complex nonlinear systems

    NASA Astrophysics Data System (ADS)

    Wang, Shi-bing; Wang, Xing-yuan; Wang, Xiu-you; Zhou, Yu-fei

    2016-04-01

    With comprehensive consideration of generalized synchronization, combination synchronization and adaptive control, this paper investigates a novel adaptive generalized combination complex synchronization (AGCCS) scheme for different real and complex nonlinear systems with unknown parameters. On the basis of Lyapunov stability theory and adaptive control, an AGCCS controller and parameter update laws are derived to achieve synchronization and parameter identification of two real drive systems and a complex response system, as well as two complex drive systems and a real response system. Two simulation examples, namely, ACGCS for chaotic real Lorenz and Chen systems driving a hyperchaotic complex Lü system, and hyperchaotic complex Lorenz and Chen systems driving a real chaotic Lü system, are presented to verify the feasibility and effectiveness of the proposed scheme.

  9. On the eigenvalue control of electromechanical oscillations by adaptive power system stabilizer

    SciTech Connect

    Ostojic, D.; Kovacevie, B. . Elektrotehnicki Fakultet)

    1990-11-01

    This paper presents the eigenvalue control strategy which utilizes an adaptive power system stabilizer for the decentralized control of damping and frequency of electromechanical oscillations in power systems. The control procedure includes the complete identification of the decoupled subsystem model in real-time from local measurements only and the assignment of its estimated electromechanical eigenvalue by the change of stabilizer parameters. The robustness and efficiency of the proposed adaptive controller to enhance overall system stability are illustrated in several examples, including the three-machine power system model.

  10. State Identification in Nonlinear Systems

    SciTech Connect

    Holloway, James Paul

    2005-02-06

    A state estimation method based on finding a system state that causes a model to match a set of system measurements is regularized by requiring that sudden changes in system state be avoided. The required optimization is accomplished by a pattern search algorithm. The method does not require derivative information or linearization of the model. Is has been applied to a 10 dimensional model of a fast reactor system.

  11. Adaptive Decision Aiding in Computer-Assisted Instruction: Adaptive Computerized Training System (ACTS).

    ERIC Educational Resources Information Center

    Hopf-Weichel, Rosemarie; And Others

    This report describes results of the first year of a three-year program to develop and evaluate a new Adaptive Computerized Training System (ACTS) for electronics maintenance training. (ACTS incorporates an adaptive computer program that learns the student's diagnostic and decision value structure, compares it to that of an expert, and adapts the…

  12. Adaptive cyber-attack modeling system

    NASA Astrophysics Data System (ADS)

    Gonsalves, Paul G.; Dougherty, Edward T.

    2006-05-01

    The pervasiveness of software and networked information systems is evident across a broad spectrum of business and government sectors. Such reliance provides an ample opportunity not only for the nefarious exploits of lone wolf computer hackers, but for more systematic software attacks from organized entities. Much effort and focus has been placed on preventing and ameliorating network and OS attacks, a concomitant emphasis is required to address protection of mission critical software. Typical software protection technique and methodology evaluation and verification and validation (V&V) involves the use of a team of subject matter experts (SMEs) to mimic potential attackers or hackers. This manpower intensive, time-consuming, and potentially cost-prohibitive approach is not amenable to performing the necessary multiple non-subjective analyses required to support quantifying software protection levels. To facilitate the evaluation and V&V of software protection solutions, we have designed and developed a prototype adaptive cyber attack modeling system. Our approach integrates an off-line mechanism for rapid construction of Bayesian belief network (BN) attack models with an on-line model instantiation, adaptation and knowledge acquisition scheme. Off-line model construction is supported via a knowledge elicitation approach for identifying key domain requirements and a process for translating these requirements into a library of BN-based cyber-attack models. On-line attack modeling and knowledge acquisition is supported via BN evidence propagation and model parameter learning.

  13. Adaptable formations utilizing heterogeneous unmanned systems

    NASA Astrophysics Data System (ADS)

    Barnes, Laura E.; Garcia, Richard; Fields, MaryAnne; Valavanis, Kimon

    2009-05-01

    This paper addresses the problem of controlling and coordinating heterogeneous unmanned systems required to move as a group while maintaining formation. We propose a strategy to coordinate groups of unmanned ground vehicles (UGVs) with one or more unmanned aerial vehicles (UAVs). UAVs can be utilized in one of two ways: (1) as alpha robots to guide the UGVs; and (2) as beta robots to surround the UGVs and adapt accordingly. In the first approach, the UAV guides a swarm of UGVs controlling their overall formation. In the second approach, the UGVs guide the UAVs controlling their formation. The unmanned systems are brought into a formation utilizing artificial potential fields generated from normal and sigmoid functions. These functions control the overall swarm geometry. Nonlinear limiting functions are defined to provide tighter swarm control by modifying and adjusting a set of control variables forcing the swarm to behave according to set constraints. Formations derived are subsets of elliptical curves but can be generalized to any curvilinear shape. Both approaches are demonstrated in simulation and experimentally. To demonstrate the second approach in simulation, a swarm of forty UAVs is utilized in a convoy protection mission. As a convoy of UGVs travels, UAVs dynamically and intelligently adapt their formation in order to protect the convoy of vehicles as it moves. Experimental results are presented to demonstrate the approach using a fully autonomous group of three UGVs and a single UAV helicopter for coordination.

  14. Continuous-Time Bilinear System Identification

    NASA Technical Reports Server (NTRS)

    Juang, Jer-Nan

    2003-01-01

    The objective of this paper is to describe a new method for identification of a continuous-time multi-input and multi-output bilinear system. The approach is to make judicious use of the linear-model properties of the bilinear system when subjected to a constant input. Two steps are required in the identification process. The first step is to use a set of pulse responses resulting from a constant input of one sample period to identify the state matrix, the output matrix, and the direct transmission matrix. The second step is to use another set of pulse responses with the same constant input over multiple sample periods to identify the input matrix and the coefficient matrices associated with the coupling terms between the state and the inputs. Numerical examples are given to illustrate the concept and the computational algorithm for the identification method.

  15. Serial identification of EEG patterns using adaptive wavelet-based analysis

    NASA Astrophysics Data System (ADS)

    Nazimov, A. I.; Pavlov, A. N.; Nazimova, A. A.; Grubov, V. V.; Koronovskii, A. A.; Sitnikova, E.; Hramov, A. E.

    2013-10-01

    A problem of recognition specific oscillatory patterns in the electroencephalograms with the continuous wavelet-transform is discussed. Aiming to improve abilities of the wavelet-based tools we propose a serial adaptive method for sequential identification of EEG patterns such as sleep spindles and spike-wave discharges. This method provides an optimal selection of parameters based on objective functions and enables to extract the most informative features of the recognized structures. Different ways of increasing the quality of patterns recognition within the proposed serial adaptive technique are considered.

  16. Frequency domain synthesis of optimal inputs for adaptive identification and control

    NASA Technical Reports Server (NTRS)

    Fu, Li-Chen; Sastry, Shankar

    1987-01-01

    The input design problem of selecting appropriate inputs for use in SISO adaptive identification and model reference adaptive control algorithms is considered. Averaging theory is used to characterize the optimal inputs in the frequency domain. The design problem is formulated as an optimization problem which maximizes the smallest eigenvalue of the average information matrix over power constrained signals, and the global optimal solution is obtained using a convergent numerical algorithm. A bound on the frequency search range required in the design algorithm has been determined in terms of the desired performance.

  17. Contrarian behavior in a complex adaptive system

    NASA Astrophysics Data System (ADS)

    Liang, Y.; An, K. N.; Yang, G.; Huang, J. P.

    2013-01-01

    Contrarian behavior is a kind of self-organization in complex adaptive systems (CASs). Here we report the existence of a transition point in a model resource-allocation CAS with contrarian behavior by using human experiments, computer simulations, and theoretical analysis. The resource ratio and system predictability serve as the tuning parameter and order parameter, respectively. The transition point helps to reveal the positive or negative role of contrarian behavior. This finding is in contrast to the common belief that contrarian behavior always has a positive role in resource allocation, say, stabilizing resource allocation by shrinking the redundancy or the lack of resources. It is further shown that resource allocation can be optimized at the transition point by adding an appropriate size of contrarians. This work is also expected to be of value to some other fields ranging from management and social science to ecology and evolution.

  18. Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS)

    NASA Technical Reports Server (NTRS)

    Masek, Jeffrey G.

    2006-01-01

    The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) project is creating a record of forest disturbance and regrowth for North America from the Landsat satellite record, in support of the carbon modeling activities. LEDAPS relies on the decadal Landsat GeoCover data set supplemented by dense image time series for selected locations. Imagery is first atmospherically corrected to surface reflectance, and then change detection algorithms are used to extract disturbance area, type, and frequency. Reuse of the MODIS Land processing system (MODAPS) architecture allows rapid throughput of over 2200 MSS, TM, and ETM+ scenes. Initial ("Beta") surface reflectance products are currently available for testing, and initial continental disturbance products will be available by the middle of 2006.

  19. Systemic Cold Stress Adaptation of Chlamydomonas reinhardtii*

    PubMed Central

    Valledor, Luis; Furuhashi, Takeshi; Hanak, Anne-Mette; Weckwerth, Wolfram

    2013-01-01

    Chlamydomonas reinhardtii is one of the most important model organisms nowadays phylogenetically situated between higher plants and animals (Merchant et al. 2007). Stress adaptation of this unicellular model algae is in the focus because of its relevance to biomass and biofuel production. Here, we have studied cold stress adaptation of C. reinhardtii hitherto not described for this algae whereas intensively studied in higher plants. Toward this goal, high throughput mass spectrometry was employed to integrate proteome, metabolome, physiological and cell-morphological changes during a time-course from 0 to 120 h. These data were complemented with RT-qPCR for target genes involved in central metabolism, signaling, and lipid biosynthesis. Using this approach dynamics in central metabolism were linked to cold-stress dependent sugar and autophagy pathways as well as novel genes in C. reinhardtii such as CKIN1, CKIN2 and a hitherto functionally not annotated protein named CKIN3. Cold stress affected extensively the physiology and the organization of the cell. Gluconeogenesis and starch biosynthesis pathways are activated leading to a pronounced starch and sugar accumulation. Quantitative lipid profiles indicate a sharp decrease in the lipophilic fraction and an increase in polyunsaturated fatty acids suggesting this as a mechanism of maintaining membrane fluidity. The proteome is completely remodeled during cold stress: specific candidates of the ribosome and the spliceosome indicate altered biosynthesis and degradation of proteins important for adaptation to low temperatures. Specific proteasome degradation may be mediated by the observed cold-specific changes in the ubiquitinylation system. Sparse partial least squares regression analysis was applied for protein correlation network analysis using proteins as predictors and Fv/Fm, FW, total lipids, and starch as responses. We applied also Granger causality analysis and revealed correlations between proteins and

  20. Parametric uncertain identification of a robotic system

    NASA Astrophysics Data System (ADS)

    Angel, L.; Viola, J.; Hernández, C.

    2016-07-01

    This paper presents the parametric uncertainties identification of a robotic system of one degree of freedom. A MSC-ADAMS / MATLAB co-simulation model was built to simulate the uncertainties that affect the robotic system. For a desired trajectory, a set of dynamic models of the system was identified in presence of variations in the mass, length and friction of the system employing least squares method. Using the input-output linearization technique a linearized model plant was defined. Finally, the maximum multiplicative uncertainty of the system was modelled giving the controller desired design conditions to achieve a robust stability and performance of the closed loop system.

  1. Optical disk uses in criminal identification systems

    NASA Astrophysics Data System (ADS)

    Sypherd, Allen D.

    1990-08-01

    A significant advancement in law enforcement tools has been made possible by the rapid and innovative development of electronic imaging for criminal identification systems. In particular, development of optical disks capable of high-capacity and random-access storage has provided a unique marriage of application and technology. Fast random access to any record, non-destructive reading of stored images, electronic sorting and transmission of images and an accepted legal basis for evidence are a few of the advantages derived from optical disk technology. This paper discusses the application of optical disk technology to both Automated Fingerprint Identification Systems (AFIS) and Automated Mugshot Retrieval Systems (AMRS). The following topics are addressed in light of AFIS and AMRS user requirements and system capabilities: Write once vs. rewritable, gray level and storage requirements, multi-volume library systems, data organization and capacity trends.

  2. Feature Space Mapping as a universal adaptive system

    NASA Astrophysics Data System (ADS)

    Duch, Włodzisław; Diercksen, Geerd H. F.

    1995-06-01

    The most popular realizations of adaptive systems are based on the neural network type of algorithms, in particular feedforward multilayered perceptrons trained by backpropagation of error procedures. In this paper an alternative approach based on multidimensional separable localized functions centered at the data clusters is proposed. In comparison with the neural networks that use delocalized transfer functions this approach allows for full control of the basins of attractors of all stationary points. Slow learning procedures are replaced by the explicit construction of the landscape function followed by the optimization of adjustable parameters using gradient techniques or genetic algorithms. Retrieving information does not require searches in multidimensional subspaces but it is factorized into a series of one-dimensional searches. Feature Space Mapping is applicable to learning not only from facts but also from general laws and may be treated as a fuzzy expert system (neurofuzzy system). The number of nodes (fuzzy rules) is growing as the network creates new nodes for novel data but the search time is sublinear in the number of rules or data clusters stored. Such a system may work as a universal classificator, approximator and reasoning system. Examples of applications for the identification of spectra (classification), intelligent databases (association) and for the analysis of simple electrical circuits (expert system type) are given.

  3. 78 FR 58785 - Unique Device Identification System

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-09-24

    ... discussed in section VII. B. ``Compliance Dates.'' FOR FURTHER INFORMATION CONTACT: Jay Crowley, UDI... device identification system, as required by section 519(f) of the FD&C Act (see 77 FR 40736). On July 9...(f) of the FD&C Act (see 77 FR 69393). The preamble to the July 2012 proposal describes...

  4. Self-adaptive iris image acquisition system

    NASA Astrophysics Data System (ADS)

    Dong, Wenbo; Sun, Zhenan; Tan, Tieniu; Qiu, Xianchao

    2008-03-01

    Iris image acquisition is the fundamental step of the iris recognition, but capturing high-resolution iris images in real-time is very difficult. The most common systems have small capture volume and demand users to fully cooperate with machines, which has become the bottleneck of iris recognition's application. In this paper, we aim at building an active iris image acquiring system which is self-adaptive to users. Two low resolution cameras are co-located in a pan-tilt-unit (PTU), for face and iris image acquisition respectively. Once the face camera detects face region in real-time video, the system controls the PTU to move towards the eye region and automatically zooms, until the iris camera captures an clear iris image for recognition. Compared with other similar works, our contribution is that we use low-resolution cameras, which can transmit image data much faster and are much cheaper than the high-resolution cameras. In the system, we use Haar-like cascaded feature to detect faces and eyes, linear transformation to predict the iris camera's position, and simple heuristic PTU control method to track eyes. A prototype device has been established, and experiments show that our system can automatically capture high-quality iris image in the range of 0.6m×0.4m×0.4m in average 3 to 5 seconds.

  5. The Limits to Adaptation: A Systems Approach

    EPA Science Inventory

    The ability to adapt to climate change is delineated by capacity thresholds, after which climate damages begin to overwhelm the adaptation response. Such thresholds depend upon physical properties (natural processes and engineering parameters), resource constraints (expressed th...

  6. Flipping Adapters for Space Launch System

    NASA Video Gallery

    The structural test article adapter is flipped at Marshall testing facility Building 4705. The turnover is an important step in finishing the machining work on the adapter, which will undergo tests...

  7. Intercellular Communication in the Adaptive Immune System

    NASA Astrophysics Data System (ADS)

    Chakraborty, Arup

    2004-03-01

    Higher organisms, like humans, have an adaptive immune system that can respond to pathogens that have not been encountered before. T lymphocytes (T cells) are the orchestrators of the adaptive immune response. They interact with cells, called antigen presenting cells (APC), that display molecular signatures of pathogens. Recently, video microscopy experiments have revealed that when T cells detect antigen on APC surfaces, a spatially patterned supramolecular assembly of different types of molecules forms in the junction between cell membranes. This recognition motif is implicated in information transfer between APC and T cells, and so, is labeled the immunological synapse. The observation of synapse formation sparked two broad questions: How does the synapse form? Why does the synapse form? I will describe progress made in answering these fundamental questions in biology by synergistic use of statistical mechanical theory/computation, chemical engineering principles, and genetic and biochemical experiments. The talk will also touch upon mechanisms that may underlie the extreme sensitivity with which T cells discriminate between self and non-self.

  8. Identification of Metabolic Pathway Systems.

    PubMed

    Dolatshahi, Sepideh; Voit, Eberhard O

    2016-01-01

    The estimation of parameters in even moderately large biological systems is a significant challenge. This challenge is greatly exacerbated if the mathematical formats of appropriate process descriptions are unknown. To address this challenge, the method of dynamic flux estimation (DFE) was proposed for the analysis of metabolic time series data. Under ideal conditions, the first phase of DFE yields numerical representations of all fluxes within a metabolic pathway system, either as values at each time point or as plots against their substrates and modulators. However, this numerical result does not reveal the mathematical format of each flux. Thus, the second phase of DFE selects functional formats that are consistent with the numerical trends obtained from the first phase. While greatly facilitating metabolic data analysis, DFE is only directly applicable if the pathway system contains as many dependent variables as fluxes. Because most actual systems contain more fluxes than metabolite pools, this requirement is seldom satisfied. Auxiliary methods have been proposed to alleviate this issue, but they are not general. Here we propose strategies that extend DFE toward general, slightly underdetermined pathway systems.

  9. Identification of Metabolic Pathway Systems

    PubMed Central

    Dolatshahi, Sepideh; Voit, Eberhard O.

    2016-01-01

    The estimation of parameters in even moderately large biological systems is a significant challenge. This challenge is greatly exacerbated if the mathematical formats of appropriate process descriptions are unknown. To address this challenge, the method of dynamic flux estimation (DFE) was proposed for the analysis of metabolic time series data. Under ideal conditions, the first phase of DFE yields numerical representations of all fluxes within a metabolic pathway system, either as values at each time point or as plots against their substrates and modulators. However, this numerical result does not reveal the mathematical format of each flux. Thus, the second phase of DFE selects functional formats that are consistent with the numerical trends obtained from the first phase. While greatly facilitating metabolic data analysis, DFE is only directly applicable if the pathway system contains as many dependent variables as fluxes. Because most actual systems contain more fluxes than metabolite pools, this requirement is seldom satisfied. Auxiliary methods have been proposed to alleviate this issue, but they are not general. Here we propose strategies that extend DFE toward general, slightly underdetermined pathway systems. PMID:26904095

  10. Adaptive and neuroadaptive control for nonnegative and compartmental dynamical systems

    NASA Astrophysics Data System (ADS)

    Volyanskyy, Kostyantyn Y.

    Neural networks have been extensively used for adaptive system identification as well as adaptive and neuroadaptive control of highly uncertain systems. The goal of adaptive and neuroadaptive control is to achieve system performance without excessive reliance on system models. To improve robustness and the speed of adaptation of adaptive and neuroadaptive controllers several controller architectures have been proposed in the literature. In this dissertation, we develop a new neuroadaptive control architecture for nonlinear uncertain dynamical systems. The proposed framework involves a novel controller architecture with additional terms in the update laws that are constructed using a moving window of the integrated system uncertainty. These terms can be used to identify the ideal system weights of the neural network as well as effectively suppress system uncertainty. Linear and nonlinear parameterizations of the system uncertainty are considered and state and output feedback neuroadaptive controllers are developed. Furthermore, we extend the developed framework to discrete-time dynamical systems. To illustrate the efficacy of the proposed approach we apply our results to an aircraft model with wing rock dynamics, a spacecraft model with unknown moment of inertia, and an unmanned combat aerial vehicle undergoing actuator failures, and compare our results with standard neuroadaptive control methods. Nonnegative systems are essential in capturing the behavior of a wide range of dynamical systems involving dynamic states whose values are nonnegative. A sub-class of nonnegative dynamical systems are compartmental systems. These systems are derived from mass and energy balance considerations and are comprised of homogeneous interconnected microscopic subsystems or compartments which exchange variable quantities of material via intercompartmental flow laws. In this dissertation, we develop direct adaptive and neuroadaptive control framework for stabilization, disturbance

  11. An efficient automatic firearm identification system

    NASA Astrophysics Data System (ADS)

    Chuan, Zun Liang; Liong, Choong-Yeun; Jemain, Abdul Aziz; Ghani, Nor Azura Md.

    2014-06-01

    Automatic firearm identification system (AFIS) is highly demanded in forensic ballistics to replace the traditional approach which uses comparison microscope and is relatively complex and time consuming. Thus, several AFIS have been developed for commercial and testing purposes. However, those AFIS are still unable to overcome some of the drawbacks of the traditional firearm identification approach. The goal of this study is to introduce another efficient and effective AFIS. A total of 747 firing pin impression images captured from five different pistols of same make and model are used to evaluate the proposed AFIS. It was demonstrated that the proposed AFIS is capable of producing firearm identification accuracy rate of over 95.0% with an execution time of less than 0.35 seconds per image.

  12. Adaptive model training system and method

    DOEpatents

    Bickford, Randall L; Palnitkar, Rahul M

    2014-11-18

    An adaptive model training system and method for filtering asset operating data values acquired from a monitored asset for selectively choosing asset operating data values that meet at least one predefined criterion of good data quality while rejecting asset operating data values that fail to meet at least the one predefined criterion of good data quality; and recalibrating a previously trained or calibrated model having a learned scope of normal operation of the asset by utilizing the asset operating data values that meet at least the one predefined criterion of good data quality for adjusting the learned scope of normal operation of the asset for defining a recalibrated model having the adjusted learned scope of normal operation of the asset.

  13. Adaptive model training system and method

    DOEpatents

    Bickford, Randall L; Palnitkar, Rahul M; Lee, Vo

    2014-04-15

    An adaptive model training system and method for filtering asset operating data values acquired from a monitored asset for selectively choosing asset operating data values that meet at least one predefined criterion of good data quality while rejecting asset operating data values that fail to meet at least the one predefined criterion of good data quality; and recalibrating a previously trained or calibrated model having a learned scope of normal operation of the asset by utilizing the asset operating data values that meet at least the one predefined criterion of good data quality for adjusting the learned scope of normal operation of the asset for defining a recalibrated model having the adjusted learned scope of normal operation of the asset.

  14. Intelligent Optical Systems Using Adaptive Optics

    NASA Technical Reports Server (NTRS)

    Clark, Natalie

    2012-01-01

    Until recently, the phrase adaptive optics generally conjured images of large deformable mirrors being integrated into telescopes to compensate for atmospheric turbulence. However, the development of smaller, cheaper devices has sparked interest for other aerospace and commercial applications. Variable focal length lenses, liquid crystal spatial light modulators, tunable filters, phase compensators, polarization compensation, and deformable mirrors are becoming increasingly useful for other imaging applications including guidance navigation and control (GNC), coronagraphs, foveated imaging, situational awareness, autonomous rendezvous and docking, non-mechanical zoom, phase diversity, and enhanced multi-spectral imaging. The active components presented here allow flexibility in the optical design, increasing performance. In addition, the intelligent optical systems presented offer advantages in size and weight and radiation tolerance.

  15. Adaptive delta modulation systems for video encoding

    NASA Technical Reports Server (NTRS)

    Lei, T.-L. R.; Scheinberg, N.; Schilling, D. L.

    1977-01-01

    This paper describes several adaptive delta modulators designed to encode video signals. One- and two-dimensional ADM algorithms are discussed and compared. Results are shown for bit rates of 2 bits/pixel, 1 bit/pixel and 0.5 bits/pixel. Pictures showing the difference between the encoded-decoded pictures and the original pictures are presented. Results are also presented to illustrate the effect of channel errors on the reconstructed picture. A two-dimensional ADM using interframe encoding is also presented. This system operates at the rate of 2 bits/pixel and produces excellent quality pictures when there is little motion. We also describe and illustrate the effect of large amounts of motion on the reconstructed picture.

  16. Simulating Astronomical Adaptive Optics Systems Using Yao

    NASA Astrophysics Data System (ADS)

    Rigaut, François; Van Dam, Marcos

    2013-12-01

    Adaptive Optics systems are at the heart of the coming Extremely Large Telescopes generation. Given the importance, complexity and required advances of these systems, being able to simulate them faithfully is key to their success, and thus to the success of the ELTs. The type of systems envisioned to be built for the ELTs cover most of the AO breeds, from NGS AO to multiple guide star Ground Layer, Laser Tomography and Multi-Conjugate AO systems, with typically a few thousand actuators. This represents a large step up from the current generation of AO systems, and accordingly a challenge for existing AO simulation packages. This is especially true as, in the past years, computer power has not been following Moore's law in its most common understanding; CPU clocks are hovering at about 3GHz. Although the use of super computers is a possible solution to run these simulations, being able to use smaller machines has obvious advantages: cost, access, environmental issues. By using optimised code in an already proven AO simulation platform, we were able to run complex ELT AO simulations on very modest machines, including laptops. The platform is YAO. In this paper, we describe YAO, its architecture, its capabilities, the ELT-specific challenges and optimisations, and finally its performance. As an example, execution speed ranges from 5 iterations per second for a 6 LGS 60x60 subapertures Shack-Hartmann Wavefront sensor Laser Tomography AO system (including full physical image formation and detector characteristics) up to over 30 iterations/s for a single NGS AO system.

  17. 33 CFR 401.20 - Automatic Identification System.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ...' maritime Differential Global Positioning System radiobeacon services; or (7) The use of a temporary unit... 33 Navigation and Navigable Waters 3 2012-07-01 2012-07-01 false Automatic Identification System... Identification System. (a) Each of the following vessels must use an Automatic Identification System...

  18. 33 CFR 401.20 - Automatic Identification System.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ...' maritime Differential Global Positioning System radiobeacon services; or (7) The use of a temporary unit... 33 Navigation and Navigable Waters 3 2013-07-01 2013-07-01 false Automatic Identification System... Identification System. (a) Each of the following vessels must use an Automatic Identification System...

  19. 33 CFR 401.20 - Automatic Identification System.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ...' maritime Differential Global Positioning System radiobeacon services; or (7) The use of a temporary unit... 33 Navigation and Navigable Waters 3 2011-07-01 2011-07-01 false Automatic Identification System... Identification System. (a) Each of the following vessels must use an Automatic Identification System...

  20. 33 CFR 401.20 - Automatic Identification System.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ...' maritime Differential Global Positioning System radiobeacon services; or (7) The use of a temporary unit... 33 Navigation and Navigable Waters 3 2014-07-01 2014-07-01 false Automatic Identification System... Identification System. (a) Each of the following vessels must use an Automatic Identification System...

  1. Important ingredients for health adaptive information systems.

    PubMed

    Senathirajah, Yalini; Bakken, Suzanne

    2011-01-01

    Healthcare information systems frequently do not truly meet clinician needs, due to the complexity, variability, and rapid change in medical contexts. Recently the internet world has been transformed by approaches commonly termed 'Web 2.0'. This paper proposes a Web 2.0 model for a healthcare adaptive architecture. The vision includes creating modular, user-composable systems which aim to make all necessary information from multiple internal and external sources available via a platform, for the user to use, arrange, recombine, author, and share at will, using rich interfaces where advisable. Clinicians can create a set of 'widgets' and 'views' which can transform data, reflect their domain knowledge and cater to their needs, using simple drag and drop interfaces without the intervention of programmers. We have built an example system, MedWISE, embodying the user-facing parts of the model. This approach to HIS is expected to have several advantages, including greater suitability to user needs (reflecting clinician rather than programmer concepts and priorities), incorporation of multiple information sources, agile reconfiguration to meet emerging situations and new treatment deployment, capture of user domain expertise and tacit knowledge, efficiencies due to workflow and human-computer interaction improvements, and greater user acceptance.

  2. Parameter identification for nonlinear aerodynamic systems

    NASA Technical Reports Server (NTRS)

    Pearson, Allan E.

    1990-01-01

    Parameter identification for nonlinear aerodynamic systems is examined. It is presumed that the underlying model can be arranged into an input/output (I/O) differential operator equation of a generic form. The algorithm estimation is especially efficient since the equation error can be integrated exactly given any I/O pair to obtain an algebraic function of the parameters. The algorithm for parameter identification was extended to the order determination problem for linear differential system. The degeneracy in a least squares estimate caused by feedback was addressed. A method of frequency analysis for determining the transfer function G(j omega) from transient I/O data was formulated using complex valued Fourier based modulating functions in contrast with the trigonometric modulating functions for the parameter estimation problem. A simulation result of applying the algorithm is given under noise-free conditions for a system with a low pass transfer function.

  3. Identification of general linear mechanical systems

    NASA Technical Reports Server (NTRS)

    Sirlin, S. W.; Longman, R. W.; Juang, J. N.

    1983-01-01

    Previous work in identification theory has been concerned with the general first order time derivative form. Linear mechanical systems, a large and important class, naturally have a second order form. This paper utilizes this additional structural information for the purpose of identification. A realization is obtained from input-output data, and then knowledge of the system input, output, and inertia matrices is used to determine a set of linear equations whereby we identify the remaining unknown system matrices. Necessary and sufficient conditions on the number, type and placement of sensors and actuators are given which guarantee identificability, and less stringent conditions are given which guarantee generic identifiability. Both a priori identifiability and a posteriori identifiability are considered, i.e., identifiability being insured prior to obtaining data, and identifiability being assured with a given data set.

  4. Structural system identification: Structural dynamics model validation

    SciTech Connect

    Red-Horse, J.R.

    1997-04-01

    Structural system identification is concerned with the development of systematic procedures and tools for developing predictive analytical models based on a physical structure`s dynamic response characteristics. It is a multidisciplinary process that involves the ability (1) to define high fidelity physics-based analysis models, (2) to acquire accurate test-derived information for physical specimens using diagnostic experiments, (3) to validate the numerical simulation model by reconciling differences that inevitably exist between the analysis model and the experimental data, and (4) to quantify uncertainties in the final system models and subsequent numerical simulations. The goal of this project was to develop structural system identification techniques and software suitable for both research and production applications in code and model validation.

  5. Microbial identification system for Space Station Freedom

    NASA Technical Reports Server (NTRS)

    Brown, Harlan D.; Scarlett, Janie B.; Skweres, Joyce A.; Fortune, Russell L.; Staples, John L.; Pierson, Duane L.

    1989-01-01

    The Environmental Health System (EHS) and Health Maintenance Facility (HMF) on Space Station Freedom will require a comprehensive microbiology capability. This requirement entails the development of an automated system to perform microbial identifications on isolates from a variety of environmental and clinical sources and, when required, to perform antimicrobial sensitivity testing. The unit currently undergoing development and testing is the Automated Microbiology System II (AMS II) built by Vitek Systems, Inc. The AMS II has successfully completed 12 months of laboratory testing and evaluation for compatibility with microgravity operation. The AMS II is a promising technology for use on Space Station Freedom.

  6. A program for identification of linear systems

    NASA Technical Reports Server (NTRS)

    Buell, J.; Kalaba, R.; Ruspini, E.; Yakush, A.

    1971-01-01

    A program has been written for the identification of parameters in certain linear systems. These systems appear in biomedical problems, particularly in compartmental models of pharmacokinetics. The method presented here assumes that some of the state variables are regularly modified by jump conditions. This simulates administration of drugs following some prescribed drug regime. Parameters are identified by a least-square fit of the linear differential system to a set of experimental observations. The method is especially suited when the interval of observation of the system is very long.

  7. In Silico and Biochemical Analysis of Physcomitrella patens Photosynthetic Antenna: Identification of Subunits which Evolved upon Land Adaptation

    PubMed Central

    Alboresi, Alessandro; Caffarri, Stefano; Nogue, Fabien; Bassi, Roberto; Morosinotto, Tomas

    2008-01-01

    Background In eukaryotes the photosynthetic antenna system is composed of subunits encoded by the light harvesting complex (Lhc) multigene family. These proteins play a key role in photosynthesis and are involved in both light harvesting and photoprotection. The moss Physcomitrella patens is a member of a lineage that diverged from seed plants early after land colonization and therefore by studying this organism, we may gain insight into adaptations to the aerial environment. Principal Findings In this study, we characterized the antenna protein multigene family in Physcomitrella patens, by sequence analysis as well as biochemical and functional investigations. Sequence identification and analysis showed that some antenna polypeptides, such as Lhcb3 and Lhcb6, are present only in land organisms, suggesting they play a role in adaptation to the sub-aerial environment. Our functional analysis which showed that photo-protective mechanisms in Physcomitrella patens are very similar to those in seed plants fits with this hypothesis. In particular, Physcomitrella patens also activates Non Photochemical Quenching upon illumination, consistent with the detection of an ortholog of the PsbS protein. As a further adaptation to terrestrial conditions, the content of Photosystem I low energy absorbing chlorophylls also increased, as demonstrated by differences in Lhca3 and Lhca4 polypeptide sequences, in vitro reconstitution experiments and low temperature fluorescence spectra. Conclusions This study highlights the role of Lhc family members in environmental adaptation and allowed proteins associated with mechanisms of stress resistance to be identified within this large family. PMID:18446222

  8. A Gamma Memory Neural Network for System Identification

    NASA Technical Reports Server (NTRS)

    Motter, Mark A.; Principe, Jose C.

    1992-01-01

    A gamma neural network topology is investigated for a system identification application. A discrete gamma memory structure is used in the input layer, providing delayed values of both the control inputs and the network output to the input layer. The discrete gamma memory structure implements a tapped dispersive delay line, with the amount of dispersion regulated by a single, adaptable parameter. The network is trained using static back propagation, but captures significant features of the system dynamics. The system dynamics identified with the network are the Mach number dynamics of the 16 Foot Transonic Tunnel at NASA Langley Research Center, Hampton, Virginia. The training data spans an operating range of Mach numbers from 0.4 to 1.3.

  9. The ALICE-HMPID Detector Control System: Its evolution towards an expert and adaptive system

    NASA Astrophysics Data System (ADS)

    De Cataldo, G.; Franco, A.; Pastore, C.; Sgura, I.; Volpe, G.

    2011-05-01

    The High Momentum Particle IDentification (HMPID) detector is a proximity focusing Ring Imaging Cherenkov (RICH) for charged hadron identification. The HMPID is based on liquid C 6F 14 as the radiator medium and on a 10 m 2 CsI coated, pad segmented photocathode of MWPCs for UV Cherenkov photon detection. To ensure full remote control, the HMPID is equipped with a detector control system (DCS) responding to industrial standards for robustness and reliability. It has been implemented using PVSS as Slow Control And Data Acquisition (SCADA) environment, Programmable Logic Controller as control devices and Finite State Machines for modular and automatic command execution. In the perspective of reducing human presence at the experiment site, this paper focuses on DCS evolution towards an expert and adaptive control system, providing, respectively, automatic error recovery and stable detector performance. HAL9000, the first prototype of the HMPID expert system, is then presented. Finally an analysis of the possible application of the adaptive features is provided.

  10. Isoplanatism in a multiconjugate adaptive optics system.

    PubMed

    Tokovinin, A; Le Louarn, M; Sarazin, M

    2000-10-01

    Turbulence correction in a large field of view by use of an adaptive optics imaging system with several deformable mirrors (DM's) conjugated to various heights is considered. The residual phase variance is computed for an optimized linear algorithm in which a correction of each turbulent layer is achieved by applying a combination of suitably smoothed and scaled input phase screens to all DM's. Finite turbulence outer scale and finite spatial resolution of the DM's are taken into account. A general expression for the isoplanatic angle thetaM of a system with M mirrors is derived in the limiting case of infinitely large apertures and Kolmogorov turbulence. Like Fried's isoplanatic angle theta0,thetaM is a function only of the turbulence vertical profile, is scalable with wavelength, and is independent of the telescope diameter. Use of angle thetaM permits the gain in the field of view due to the increased number of DM's to be quantified and their optimal conjugate heights to be found. Calculations with real turbulence profiles show that with three DM's a gain of 7-10x is possible, giving the typical and best isoplanatic field-of-view radii of 16 and 30 arcseconds, respectively, at lambda = 0.5 microm. It is shown that in the actual systems the isoplanatic field will be somewhat larger than thetaM owing to the combined effects of finite aperture diameter, finite outer scale, and optimized wave-front spatial filtering. However, this additional gain is not dramatic; it is less than 1.5x for large-aperture telescopes. PMID:11028530

  11. Isoplanatism in a multiconjugate adaptive optics system.

    PubMed

    Tokovinin, A; Le Louarn, M; Sarazin, M

    2000-10-01

    Turbulence correction in a large field of view by use of an adaptive optics imaging system with several deformable mirrors (DM's) conjugated to various heights is considered. The residual phase variance is computed for an optimized linear algorithm in which a correction of each turbulent layer is achieved by applying a combination of suitably smoothed and scaled input phase screens to all DM's. Finite turbulence outer scale and finite spatial resolution of the DM's are taken into account. A general expression for the isoplanatic angle thetaM of a system with M mirrors is derived in the limiting case of infinitely large apertures and Kolmogorov turbulence. Like Fried's isoplanatic angle theta0,thetaM is a function only of the turbulence vertical profile, is scalable with wavelength, and is independent of the telescope diameter. Use of angle thetaM permits the gain in the field of view due to the increased number of DM's to be quantified and their optimal conjugate heights to be found. Calculations with real turbulence profiles show that with three DM's a gain of 7-10x is possible, giving the typical and best isoplanatic field-of-view radii of 16 and 30 arcseconds, respectively, at lambda = 0.5 microm. It is shown that in the actual systems the isoplanatic field will be somewhat larger than thetaM owing to the combined effects of finite aperture diameter, finite outer scale, and optimized wave-front spatial filtering. However, this additional gain is not dramatic; it is less than 1.5x for large-aperture telescopes.

  12. Identification of dynamic systems, theory and formulation

    NASA Technical Reports Server (NTRS)

    Maine, R. E.; Iliff, K. W.

    1985-01-01

    The problem of estimating parameters of dynamic systems is addressed in order to present the theoretical basis of system identification and parameter estimation in a manner that is complete and rigorous, yet understandable with minimal prerequisites. Maximum likelihood and related estimators are highlighted. The approach used requires familiarity with calculus, linear algebra, and probability, but does not require knowledge of stochastic processes or functional analysis. The treatment emphasizes unification of the various areas in estimation in dynamic systems is treated as a direct outgrowth of the static system theory. Topics covered include basic concepts and definitions; numerical optimization methods; probability; statistical estimators; estimation in static systems; stochastic processes; state estimation in dynamic systems; output error, filter error, and equation error methods of parameter estimation in dynamic systems, and the accuracy of the estimates.

  13. Implementation of an Adaptive Learning System Using a Bayesian Network

    ERIC Educational Resources Information Center

    Yasuda, Keiji; Kawashima, Hiroyuki; Hata, Yoko; Kimura, Hiroaki

    2015-01-01

    An adaptive learning system is proposed that incorporates a Bayesian network to efficiently gauge learners' understanding at the course-unit level. Also, learners receive content that is adapted to their measured level of understanding. The system works on an iPad via the Edmodo platform. A field experiment using the system in an elementary school…

  14. Valuation of design adaptability in aerospace systems

    NASA Astrophysics Data System (ADS)

    Fernandez Martin, Ismael

    As more information is brought into early stages of the design, more pressure is put on engineers to produce a reliable, high quality, and financially sustainable product. Unfortunately, requirements established at the beginning of a new project by customers, and the environment that surrounds them, continue to change in some unpredictable ways. The risk of designing a system that may become obsolete during early stages of production is currently tackled by the use of robust design simulation, a method that allows to simultaneously explore a plethora of design alternatives and requirements with the intention of accounting for uncertain factors in the future. Whereas this design technique has proven to be quite an improvement in design methods, under certain conditions, it fails to account for the change of uncertainty over time and the intrinsic value embedded in the system when certain design features are activated. This thesis introduces the concepts of adaptability and real options to manage risk foreseen in the face of uncertainty at early design stages. The method described herein allows decision-makers to foresee the financial impact of their decisions at the design level, as well as the final exposure to risk. In this thesis, cash flow models, traditionally used to obtain the forecast of a project's value over the years, were replaced with surrogate models that are capable of showing fluctuations on value every few days. This allowed a better implementation of real options valuation, optimization, and strategy selection. Through the option analysis model, an optimization exercise allows the user to obtain the best implementation strategy in the face of uncertainty as well as the overall value of the design feature. Here implementation strategy refers to the decision to include a new design feature in the system, after the design has been finalized, but before the end of its production life. The ability to do this in a cost efficient manner after the system

  15. Adapt

    NASA Astrophysics Data System (ADS)

    Bargatze, L. F.

    2015-12-01

    Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted

  16. Network and adaptive system of systems modeling and analysis.

    SciTech Connect

    Lawton, Craig R.; Campbell, James E. Dr.; Anderson, Dennis James; Eddy, John P.

    2007-05-01

    This report documents the results of an LDRD program entitled ''Network and Adaptive System of Systems Modeling and Analysis'' that was conducted during FY 2005 and FY 2006. The purpose of this study was to determine and implement ways to incorporate network communications modeling into existing System of Systems (SoS) modeling capabilities. Current SoS modeling, particularly for the Future Combat Systems (FCS) program, is conducted under the assumption that communication between the various systems is always possible and occurs instantaneously. A more realistic representation of these communications allows for better, more accurate simulation results. The current approach to meeting this objective has been to use existing capabilities to model network hardware reliability and adding capabilities to use that information to model the impact on the sustainment supply chain and operational availability.

  17. Central nervous system adaptation to exercise training

    NASA Astrophysics Data System (ADS)

    Kaminski, Lois Anne

    Exercise training causes physiological changes in skeletal muscle that results in enhanced performance in humans and animals. Despite numerous studies on exercise effects on skeletal muscle, relatively little is known about adaptive changes in the central nervous system. This study investigated whether spinal pathways that mediate locomotor activity undergo functional adaptation after 28 days of exercise training. Ventral horn spinal cord expression of calcitonin gene-related peptide (CGRP), a trophic factor at the neuromuscular junction, choline acetyltransferase (Chat), the synthetic enzyme for acetylcholine, vesicular acetylcholine transporter (Vacht), a transporter of ACh into synaptic vesicles and calcineurin (CaN), a protein phosphatase that phosphorylates ion channels and exocytosis machinery were measured to determine if changes in expression occurred in response to physical activity. Expression of these proteins was determined by western blot and immunohistochemistry (IHC). Comparisons between sedentary controls and animals that underwent either endurance training or resistance training were made. Control rats received no exercise other than normal cage activity. Endurance-trained rats were exercised 6 days/wk at 31m/min on a treadmill (8% incline) for 100 minutes. Resistance-trained rats supported their weight plus an additional load (70--80% body weight) on a 60° incline (3 x 3 min, 5 days/wk). CGRP expression was measured by radioimmunoassay (RIA). CGRP expression in the spinal dorsal and ventral horn of exercise-trained animals was not significantly different than controls. Chat expression measured by Western blot and IHC was not significantly different between runners and controls but expression in resistance-trained animals assayed by IHC was significantly less than controls and runners. Vacht and CaN immunoreactivity in motor neurons of endurance-trained rats was significantly elevated relative to control and resistance-trained animals. Ventral

  18. Power system identification toolbox: Phase two progress

    SciTech Connect

    Trudnowski, D.J.

    1994-08-01

    This report describes current progress on a project funded by the Bonneville Power Administration (BPA) to develop a set of state-of-the-art analysis software (termed the Power System Identification [PSI] Toolbox) for fitting dynamic models to measured data. The project is being conducted as a three-phase effort. The first phase, completed in late 1992, involved investigating the characteristics of the analysis techniques by evaluating existing software and developing guidelines for best use. Phase Two includes extending current software, developing new analysis algorithms and software, and demonstrating and developing applications. The final phase will focus on reorganizing the software into a modular collection of documented computer programs and developing user manuals with instruction and application guidelines. Phase Two is approximately 50% complete; progress to date and a vision for the final product of the PSI Toolbox are described. The needs of the power industry for specialized system identification methods are particularly acute. The industry is currently pushing to operate transmission systems much closer to theoretical limits by using real-time, large-scale control systems to dictate power flows and maintain dynamic stability. Reliably maintaining stability requires extensive system-dynamic modeling and analysis capability, including measurement-based methods. To serve this need, the BPA has developed specialized system-identification computer codes through in-house efforts and university contract research over the last several years. To make full integrated use of the codes, as well as other techniques, the BPA has commissioned Pacific Northwest Laboratory (PNL) to further develop the codes and techniques into the PSI Toolbox.

  19. Wiener-Hammerstein system identification - an evolutionary approach

    NASA Astrophysics Data System (ADS)

    Naitali, Abdessamad; Giri, Fouad

    2016-01-01

    The problem of identifying parametric Wiener-Hammerstein (WH) systems is addressed within the evolutionary optimisation context. Specifically, a hybrid culture identification method is developed that involves model structure adaptation using genetic recombination and model parameter learning using particle swarm optimisation. The method enjoys three interesting features: (1) the risk of premature convergence of model parameter estimates to local optima is significantly reduced, due to the constantly maintained diversity of model candidates; (2) no prior knowledge is needed except for upper bounds on the system structure indices; (3) the method is fully autonomous as no interaction is needed with the user during the optimum search process. The performances of the proposed method will be illustrated and compared to alternative methods using a well-established WH benchmark.

  20. Intellectual system of identification of Arabic graphics

    NASA Astrophysics Data System (ADS)

    Abdoullayeva, Gulchin G.; Aliyev, Telman A.; Gurbanova, Nazakat G.

    2001-08-01

    The studies made by using the domain of graphic images allowed creating facilities of the artificial intelligence for letters, letter combinations etc. for various graphics and prints. The work proposes a system of recognition and identification of symbols of the Arabic graphics, which has its own specificity as compared to Latin and Cyrillic ones. The starting stage of the recognition and the identification is coding with further entry of information into a computer. Here the problem of entry is one of the essentials. For entry of a large volume of information in the unit of time a scanner is usually employed. Along with the scanner the authors suggest their elaboration of technical facilities for effective input and coding of the information. For refinement of symbols not identified from the scanner mostly for a small bulk of information the developed coding devices are used directly in the process of writing. The functional design of the software is elaborated on the basis of the heuristic model of the creative activity of a researcher and experts in the description and estimation of states of the weakly formalizable systems on the strength of the methods of identification and of selection of geometric features.

  1. Aircraft as adaptive nonlinear system which must be in the adaptational maximum zone for safety

    SciTech Connect

    Ignative, M.; Simatos, N.; Sivasundaram, S.

    1994-12-31

    Safety is a main problem in aircraft. We are considering this problem from the point of view related to existence of the adaptational maximum in complex developing systems. Safety space of aircraft parameters are determined. This space is transformed to different regimes of flight, when one engine malfunctions etc., are considered. Also it is shown that maximum safety is in adaptational maximum zone.

  2. A framework for constructing adaptive and reconfigurable systems

    SciTech Connect

    Poirot, Pierre-Etienne; Nogiec, Jerzy; Ren, Shangping; /IIT, Chicago

    2007-05-01

    This paper presents a software approach to augmenting existing real-time systems with self-adaptation capabilities. In this approach, based on the control loop paradigm commonly used in industrial control, self-adaptation is decomposed into observing system events, inferring necessary changes based on a system's functional model, and activating appropriate adaptation procedures. The solution adopts an architectural decomposition that emphasizes independence and separation of concerns. It encapsulates observation, modeling and correction into separate modules to allow for easier customization of the adaptive behavior and flexibility in selecting implementation technologies.

  3. CRISPR adaptation in Escherichia coli subtypeI-E system.

    PubMed

    Kiro, Ruth; Goren, Moran G; Yosef, Ido; Qimron, Udi

    2013-12-01

    The CRISPRs (clustered regularly interspaced short palindromic repeats) and their associated Cas (CRISPR-associated) proteins are a prokaryotic adaptive defence system against foreign nucleic acids. The CRISPR array comprises short repeats flanking short segments, called 'spacers', which are derived from foreign nucleic acids. The process of spacer insertion into the CRISPR array is termed 'adaptation'. Adaptation allows the system to rapidly evolve against emerging threats. In the present article, we review the most recent studies on the adaptation process, and focus primarily on the subtype I-E CRISPR-Cas system of Escherichia coli.

  4. Nonequilibrium Enhances Adaptation Efficiency of Stochastic Biochemical Systems

    PubMed Central

    Jia, Chen; Qian, Minping

    2016-01-01

    Adaptation is a crucial biological function possessed by many sensory systems. Early work has shown that some influential equilibrium models can achieve accurate adaptation. However, recent studies indicate that there are close relationships between adaptation and nonequilibrium. In this paper, we provide an explanation of these two seemingly contradictory results based on Markov models with relatively simple networks. We show that as the nonequilibrium driving becomes stronger, the system under consideration will undergo a phase transition along a fixed direction: from non-adaptation to simple adaptation then to oscillatory adaptation, while the transition in the opposite direction is forbidden. This indicates that although adaptation may be observed in equilibrium systems, it tends to occur in systems far away from equilibrium. In addition, we find that nonequilibrium will improve the performance of adaptation by enhancing the adaptation efficiency. All these results provide a deeper insight into the connection between adaptation and nonequilibrium. Finally, we use a more complicated network model of bacterial chemotaxis to validate the main results of this paper. PMID:27195482

  5. Sinusoidal error perturbation reveals multiple coordinate systems for sensorymotor adaptation.

    PubMed

    Hudson, Todd E; Landy, Michael S

    2016-02-01

    A coordinate system is composed of an encoding, defining the dimensions of the space, and an origin. We examine the coordinate encoding used to update motor plans during sensory-motor adaptation to center-out reaches. Adaptation is induced using a novel paradigm in which feedback of reach endpoints is perturbed following a sinewave pattern over trials; the perturbed dimensions of the feedback were the axes of a Cartesian coordinate system in one session and a polar coordinate system in another session. For center-out reaches to randomly chosen target locations, reach errors observed at one target will require different corrections at other targets within Cartesian- and polar-coded systems. The sinewave adaptation technique allowed us to simultaneously adapt both dimensions of each coordinate system (x-y, or reach gain and angle), and identify the contributions of each perturbed dimension by adapting each at a distinct temporal frequency. The efficiency of this technique further allowed us to employ perturbations that were a fraction the size normally used, which avoids confounding automatic adaptive processes with deliberate adjustments made in response to obvious experimental manipulations. Subjects independently corrected errors in each coordinate in both sessions, suggesting that the nervous system encodes both a Cartesian- and polar-coordinate-based internal representation for motor adaptation. The gains and phase lags of the adaptive responses are not readily explained by current theories of sensory-motor adaptation.

  6. A novel algorithm for real-time adaptive signal detection and identification

    SciTech Connect

    Sleefe, G.E.; Ladd, M.D.; Gallegos, D.E.; Sicking, C.W.; Erteza, I.A.

    1998-04-01

    This paper describes a novel digital signal processing algorithm for adaptively detecting and identifying signals buried in noise. The algorithm continually computes and updates the long-term statistics and spectral characteristics of the background noise. Using this noise model, a set of adaptive thresholds and matched digital filters are implemented to enhance and detect signals that are buried in the noise. The algorithm furthermore automatically suppresses coherent noise sources and adapts to time-varying signal conditions. Signal detection is performed in both the time-domain and the frequency-domain, thereby permitting the detection of both broad-band transients and narrow-band signals. The detection algorithm also provides for the computation of important signal features such as amplitude, timing, and phase information. Signal identification is achieved through a combination of frequency-domain template matching and spectral peak picking. The algorithm described herein is well suited for real-time implementation on digital signal processing hardware. This paper presents the theory of the adaptive algorithm, provides an algorithmic block diagram, and demonstrate its implementation and performance with real-world data. The computational efficiency of the algorithm is demonstrated through benchmarks on specific DSP hardware. The applications for this algorithm, which range from vibration analysis to real-time image processing, are also discussed.

  7. Restricted Complexity Framework for Nonlinear Adaptive Control in Complex Systems

    NASA Astrophysics Data System (ADS)

    Williams, Rube B.

    2004-02-01

    Control law adaptation that includes implicit or explicit adaptive state estimation, can be a fundamental underpinning for the success of intelligent control in complex systems, particularly during subsystem failures, where vital system states and parameters can be impractical or impossible to measure directly. A practical algorithm is proposed for adaptive state filtering and control in nonlinear dynamic systems when the state equations are unknown or are too complex to model analytically. The state equations and inverse plant model are approximated by using neural networks. A framework for a neural network based nonlinear dynamic inversion control law is proposed, as an extrapolation of prior developed restricted complexity methodology used to formulate the adaptive state filter. Examples of adaptive filter performance are presented for an SSME simulation with high pressure turbine failure to support extrapolations to adaptive control problems.

  8. Restricted Complexity Framework for Nonlinear Adaptive Control in Complex Systems

    SciTech Connect

    Williams, Rube B.

    2004-02-04

    Control law adaptation that includes implicit or explicit adaptive state estimation, can be a fundamental underpinning for the success of intelligent control in complex systems, particularly during subsystem failures, where vital system states and parameters can be impractical or impossible to measure directly. A practical algorithm is proposed for adaptive state filtering and control in nonlinear dynamic systems when the state equations are unknown or are too complex to model analytically. The state equations and inverse plant model are approximated by using neural networks. A framework for a neural network based nonlinear dynamic inversion control law is proposed, as an extrapolation of prior developed restricted complexity methodology used to formulate the adaptive state filter. Examples of adaptive filter performance are presented for an SSME simulation with high pressure turbine failure to support extrapolations to adaptive control problems.

  9. Boundedness of the solutions for certain classes of fractional differential equations with application to adaptive systems.

    PubMed

    Aguila-Camacho, Norelys; Duarte-Mermoud, Manuel A

    2016-01-01

    This paper presents the analysis of three classes of fractional differential equations appearing in the field of fractional adaptive systems, for the case when the fractional order is in the interval α ∈(0,1] and the Caputo definition for fractional derivatives is used. The boundedness of the solutions is proved for all three cases, and the convergence to zero of the mean value of one of the variables is also proved. Applications of the obtained results to fractional adaptive schemes in the context of identification and control problems are presented at the end of the paper, including numerical simulations which support the analytical results.

  10. Development of Adaptive Kanji Learning System for Mobile Phone

    ERIC Educational Resources Information Center

    Li, Mengmeng; Ogata, Hiroaki; Hou, Bin; Hashimoto, Satoshi; Liu, Yuqin; Uosaki, Noriko; Yano, Yoneo

    2010-01-01

    This paper describes an adaptive learning system based on mobile phone email to support the study of Japanese Kanji. In this study, the main emphasis is on using the adaptive learning to resolve one common problem of the mobile-based email or SMS language learning systems. To achieve this goal, the authors main efforts focus on three aspects:…

  11. Adaptive Hypermedia Educational System Based on XML Technologies.

    ERIC Educational Resources Information Center

    Baek, Yeongtae; Wang, Changjong; Lee, Sehoon

    This paper proposes an adaptive hypermedia educational system using XML technologies, such as XML, XSL, XSLT, and XLink. Adaptive systems are capable of altering the presentation of the content of the hypermedia on the basis of a dynamic understanding of the individual user. The user profile can be collected in a user model, while the knowledge…

  12. Management Strategies for Complex Adaptive Systems: Sensemaking, Learning, and Improvisation

    ERIC Educational Resources Information Center

    McDaniel, Reuben R., Jr.

    2007-01-01

    Misspecification of the nature of organizations may be a major reason for difficulty in achieving performance improvement. Organizations are often viewed as machine-like, but complexity science suggests that organizations should be viewed as complex adaptive systems. I identify the characteristics of complex adaptive systems and give examples of…

  13. A unique approach to the development of adaptive sensor systems for future spacecraft

    NASA Technical Reports Server (NTRS)

    Schappell, R. T.; Tietz, J. C.; Sivertson, W. E.; Wilson, R. G.

    1979-01-01

    In the Shuttle era, it should be possible to develop adaptive remote sensor systems serving more directly specific researcher and user needs and at the same time alleviating the data management problem via intelligent sensor capabilities. The present paper provides a summary of such an approach, wherein specific capabilities have been developed for future global monitoring applications. A detailed description of FILE-I (Feature Identification and Location Experiment) is included along with a summary of future experiments currently under development.

  14. Adaptable System for Vehicle Health and Usage Monitoring

    NASA Technical Reports Server (NTRS)

    Woodart, Stanley E.; Woodman, Keith L.; Coffey, Neil C.; Taylor, Bryant D.

    2005-01-01

    Aircraft and other vehicles are often kept in service beyond their original design lives. As they age, they become susceptible to system malfunctions and fatigue. Unlike future aircraft that will include health-monitoring capabilities as integral parts in their designs, older aircraft have not been so equipped. The Adaptable Vehicle Health and Usage Monitoring System is designed to be retrofitted into a preexisting fleet of military and commercial aircraft, ships, or ground vehicles to provide them with state-of-the-art health- and usage-monitoring capabilities. The monitoring system is self-contained, and the integration of it into existing systems entails limited intrusion. In essence, it has bolt-on/ bolt-off simplicity that makes it easy to install on any preexisting vehicle or structure. Because the system is completely independent of the vehicle, it can be certified for airworthiness as an independent system. The purpose served by the health-monitoring system is to reduce vehicle operating costs and to increase safety and reliability. The monitoring system is a means to identify damage to, or deterioration of, vehicle subsystems, before such damage or deterioration becomes costly and/or disastrous. Frequent monitoring of a vehicle enables identification of the embryonic stages of damage or deterioration. The knowledge thus gained can be used to correct anomalies while they are still somewhat minor. Maintenance can be performed as needed, instead of having the need for maintenance identified during cyclic inspections that take vehicles off duty even when there are no maintenance problems. Measurements and analyses acquired by the health-monitoring system also can be used to analyze mishaps. Overall, vehicles can be made more reliable and kept on duty for longer times. Figure 1 schematically depicts the system as applied to a fleet of n vehicles. The system has three operational levels. All communication between system components is by use of wireless

  15. Robust uncertainty evaluation for system identification on distributed wireless platforms

    NASA Astrophysics Data System (ADS)

    Crinière, Antoine; Döhler, Michael; Le Cam, Vincent; Mevel, Laurent

    2016-04-01

    Health monitoring of civil structures by system identification procedures from automatic control is now accepted as a valid approach. These methods provide frequencies and modeshapes from the structure over time. For a continuous monitoring the excitation of a structure is usually ambient, thus unknown and assumed to be noise. Hence, all estimates from the vibration measurements are realizations of random variables with inherent uncertainty due to (unknown) process and measurement noise and finite data length. The underlying algorithms are usually running under Matlab under the assumption of large memory pool and considerable computational power. Even under these premises, computational and memory usage are heavy and not realistic for being embedded in on-site sensor platforms such as the PEGASE platform. Moreover, the current push for distributed wireless systems calls for algorithmic adaptation for lowering data exchanges and maximizing local processing. Finally, the recent breakthrough in system identification allows us to process both frequency information and its related uncertainty together from one and only one data sequence, at the expense of computational and memory explosion that require even more careful attention than before. The current approach will focus on presenting a system identification procedure called multi-setup subspace identification that allows to process both frequencies and their related variances from a set of interconnected wireless systems with all computation running locally within the limited memory pool of each system before being merged on a host supervisor. Careful attention will be given to data exchanges and I/O satisfying OGC standards, as well as minimizing memory footprints and maximizing computational efficiency. Those systems are built in a way of autonomous operations on field and could be later included in a wide distributed architecture such as the Cloud2SM project. The usefulness of these strategies is illustrated on

  16. Automated Firearms Identification System (AFIDS), phase 1

    NASA Technical Reports Server (NTRS)

    Blackwell, R. J.; Framan, E. P.

    1974-01-01

    Items critical to the future development of an automated firearms identification system (AFIDS) have been examined, with the following specific results: (1) Types of objective data, that can be utilized to help establish a more factual basis for determining identity and nonidentity between pairs of fired bullets, have been identified. (2) A simulation study has indicated that randomly produced lines, similar in nature to the individual striations on a fired bullet, can be modeled and that random sequences, when compared to each other, have predictable relationships. (3) A schematic diagram of the general concept for AFIDS has been developed and individual elements of this system have been briefly tested for feasibility. Future implementation of such a proposed system will depend on such factors as speed, utility, projected total cost and user requirements for growth. The success of the proposed system, when operational, would depend heavily on existing firearms examiners.

  17. Making adaptable systems work for mission operations: A case study

    NASA Technical Reports Server (NTRS)

    Holder, Barbara E.; Levesque, Michael E.

    1993-01-01

    The Advanced Multimission Operations System (AMMOS) at NASA's Jet Propulsion Laboratory is based on a highly adaptable multimission ground data system (MGDS) for mission operations. The goal for MGDS is to support current flight project science and engineering personnel and to meet the demands of future missions while reducing associated operations and software development costs. MGDS has become a powerful and flexible mission operations system by using a network of heterogeneous workstations, emerging open system standards, and selecting an adaptable tools-based architecture. Challenges in developing adaptable systems for mission operations and the benefits of this approach are described.

  18. Calibrated Methodology for Assessing Adaptation Costs for Urban Drainage Systems

    EPA Science Inventory

    Changes in precipitation patterns associated with climate change may pose significant challenges for storm water management systems across much of the U.S. In particular, adapting these systems to more intense rainfall events will require significant investment. The assessment ...

  19. Adaptive control of nonlinear systems with actuator failures and uncertainties

    NASA Astrophysics Data System (ADS)

    Tang, Xidong

    2005-11-01

    Actuator failures have damaging effect on the performance of control systems, leading to undesired system behavior or even instability. Actuator failures are unknown in terms of failure time instants, failure patterns, and failure parameters. For system safety and reliability, the compensation of actuator failures is of both theoretical and practical significance. This dissertation is to further the study of adaptive designs for actuator failure compensation to nonlinear systems. In this dissertation a theoretical framework for adaptive control of nonlinear systems with actuator failures and system uncertainties is established. The contributions are the development of new adaptive nonlinear control schemes to handle unknown actuator failures for convergent tracking performance, the specification of conditions as a guideline for applications and system designs, and the extension of the adaptive nonlinear control theory. In the dissertation, adaptive actuator failure compensation is studied for several classes of nonlinear systems. In particular, adaptive state feedback schemes are developed for feedback linearizable systems and parametric strict-feedback systems. Adaptive output feedback schemes are deigned for output-feedback systems and a class of systems with unknown state-dependent nonlinearities. Furthermore, adaptive designs are addressed for MIMO systems with actuator failures, based on two grouping techniques: fixed grouping and virtual grouping. Theoretical issues such as controller structures, actuation schemes, zero dynamics, observation, grouping conditions, closed-loop stability, and tracking performance are extensively investigated. For each scheme, design conditions are clarified, and detailed stability and performance analysis is presented. A variety of applications including a wing-rock model, twin otter aircraft, hypersonic aircraft, and cooperative multiple manipulators are addressed with simulation results showing the effectiveness of the

  20. Unscented Kalman filtering for wave energy converters system identification

    NASA Astrophysics Data System (ADS)

    Bakar, Mohd Aftar Abu; Green, David A.; Metcalfe, Andrew V.; Ariff, Noratiqah Mohd

    2014-06-01

    A model for a oscillating flap wave energy converter (WEC) is as a single degree of freedom system with a non-linear term to allow for the drag of the device through the water, known as the Morison term. The focus of this system identification is on estimating the dynamic state of the system and estimating the non-linear parameter from observations of the wave elevation and the vertical displacement of the device. It is assumed that the mass, stiffness and damping of the system, without the Morison term, are known from the physical characteristics of the device. The Kalman Filter (KF) can be used to estimate the states of a linear system, however, it is not directly applicable to a non-linear system. Various adaptations have been proposed for non-linear systems. One of the first was the extended Kalman Filter (EKF) which relied on a linearization about the current state values. However, an alternative approach, known as the unscented Kalman Filter (UKF) has been found to give a better performance and is easier to implement. We apply the UKF to estimate the dynamic states of the system together with the non-linear parameter. The fitted model can be used to predict the performance of the device in different wave environments.

  1. Adaptive Learning Systems: Beyond Teaching Machines

    ERIC Educational Resources Information Center

    Kara, Nuri; Sevim, Nese

    2013-01-01

    Since 1950s, teaching machines have changed a lot. Today, we have different ideas about how people learn, what instructor should do to help students during their learning process. We have adaptive learning technologies that can create much more student oriented learning environments. The purpose of this article is to present these changes and its…

  2. A Guide to Computer Adaptive Testing Systems

    ERIC Educational Resources Information Center

    Davey, Tim

    2011-01-01

    Some brand names are used generically to describe an entire class of products that perform the same function. "Kleenex," "Xerox," "Thermos," and "Band-Aid" are good examples. The term "computerized adaptive testing" (CAT) is similar in that it is often applied uniformly across a diverse family of testing methods. Although the various members of…

  3. Hormesis and adaptive cellular control systems

    EPA Science Inventory

    Hormetic dose response occurs for many endpoints associated with exposures of biological organisms to environmental stressors. Cell-based U- or inverted U-shaped responses may derive from common processes involved in activation of adaptive responses required to protect cells from...

  4. Autonomous Frequency-Domain System-Identification Program

    NASA Technical Reports Server (NTRS)

    Yam, Yeung; Mettler, Edward; Bayard, David S.; Hadaegh, Fred Y.; Milman, Mark H.; Scheid, Robert E.

    1993-01-01

    Autonomous Frequency Domain Identification (AU-FREDI) computer program implements system of methods, algorithms, and software developed for identification of parameters of mathematical models of dynamics of flexible structures and characterization, by use of system transfer functions, of such models, dynamics, and structures regarded as systems. Software considered collection of routines modified and reassembled to suit system-identification and control experiments on large flexible structures.

  5. Systems and Methods for Derivative-Free Adaptive Control

    NASA Technical Reports Server (NTRS)

    Yucelen, Tansel (Inventor); Kim, Kilsoo (Inventor); Calise, Anthony J. (Inventor)

    2015-01-01

    An adaptive control system is disclosed. The control system can control uncertain dynamic systems. The control system can employ one or more derivative-free adaptive control architectures. The control system can further employ one or more derivative-free weight update laws. The derivative-free weight update laws can comprise a time-varying estimate of an ideal vector of weights. The control system of the present invention can therefore quickly stabilize systems that undergo sudden changes in dynamics, caused by, for example, sudden changes in weight. Embodiments of the present invention can also provide a less complex control system than existing adaptive control systems. The control system can control aircraft and other dynamic systems, such as, for example, those with non-minimum phase dynamics.

  6. SYSTEM IDENTIFICATION OF THE LINAC RF SYSTEM USING A WAVELET METHOD AND ITS APPLICATIONS IN THE SNS LLRF CONTROL SYSTEM

    SciTech Connect

    Y. WANG; S. KWON; ET AL

    2001-06-01

    For a pulsed LINAC such as the SNS, an adaptive feed-forward algorithm plays an important role in reducing the repetitive disturbance caused by the pulsed operation conditions. In most modern feed-forward control algorithms, accurate real time system identification is required to make the algorithm more effective. In this paper, an efficient wavelet method is applied to the system identification in which the Haar function is used as the base wavelet. The advantage of this method is that the Fourier transform of the Haar function in the time domain is a sine function in the frequency domain. Thus we can directly obtain the system transfer function in the frequency domain from the coefficients of the time domain system response.

  7. Adaptive management of social-ecological systems: the path forward

    USGS Publications Warehouse

    Allen, Craig R.

    2015-01-01

    Adaptive management remains at the forefront of environmental management nearly 40 years after its original conception, largely because we have yet to develop other methodologies that offer the same promise. Despite the criticisms of adaptive management and the numerous failed attempts to implement it, adaptive management has yet to be replaced with a better alternative. The concept persists because it is simple, allows action despite uncertainty, and fosters learning. Moving forward, adaptive management of social-ecological systems provides policymakers, managers and scientists a powerful tool for managing for resilience in the face of uncertainty.

  8. Adaptation of a coculture technique to the Minitek anaerobe system.

    PubMed Central

    Hussain, Z; Lannigan, R; Bürger, H; Groves, D

    1985-01-01

    A method to produce anaerobic conditions by coculture with a nonfermentative organism was utilized in conjunction with the Minitek anaerobe system (BBL Microbiology Systems, Cockeysville, Md.) for identification of anaerobic bacteria from clinical specimens. With the coculture method, the Minitek anaerobe identification tests could be incubated under aerobic conditions. In 1,900 individual biochemical reactions, 1,826 (96%) were identical whether anaerobic conditions were achieved by conventional or coculture techniques. In comparison with the reference identification (Virginia Polytechnic Institute and State University, Blacksburg), both systems of incubation identified 91 of 99 strains (92%) correctly. The method of incubation had an effect on identification to the genus level in 1 of 99 (1%) strains and to the species level in 3 of 99 (3%) strains. PMID:3886697

  9. Adaptive control applied to Space Station attitude control system

    NASA Technical Reports Server (NTRS)

    Lam, Quang M.; Chipman, Richard; Hu, Tsay-Hsin G.; Holmes, Eric B.; Sunkel, John

    1992-01-01

    This paper presents an adaptive control approach to enhance the performance of current attitude control system used by the Space Station Freedom. The proposed control law was developed based on the direct adaptive control or model reference adaptive control scheme. Performance comparisons, subject to inertia variation, of the adaptive controller and the fixed-gain linear quadratic regulator currently implemented for the Space Station are conducted. Both the fixed-gain and the adaptive gain controllers are able to maintain the Station stability for inertia variations of up to 35 percent. However, when a 50 percent inertia variation is applied to the Station, only the adaptive controller is able to maintain the Station attitude.

  10. System Identification of a Vortex Lattice Aerodynamic Model

    NASA Technical Reports Server (NTRS)

    Juang, Jer-Nan; Kholodar, Denis; Dowell, Earl H.

    2001-01-01

    The state-space presentation of an aerodynamic vortex model is considered from a classical and system identification perspective. Using an aerodynamic vortex model as a numerical simulator of a wing tunnel experiment, both full state and limited state data or measurements are considered. Two possible approaches for system identification are presented and modal controllability and observability are also considered. The theory then is applied to the system identification of a flow over an aerodynamic delta wing and typical results are presented.

  11. Nonlinear identification of ionic polymer actuator systems

    NASA Astrophysics Data System (ADS)

    Kothera, Curt S.; Lacy, Seth L.; Erwin, R. Scott; Leo, Donald J.

    2004-07-01

    Ionic polymers are a class of electromechanically coupled materials that can be used as flexible transducers. When set up in the cantilever configuration, the actuators exhibit a large bending deflection when an electric field is applied across their thickness. Being a relatively new research topic, the governing physical and chemical mechanisms are not yet fully understood. Experimental results have demonstrated nonlinear dynamic behavior. The nonlinear dynamics can be seen in the response of current, displacement, and velocity of the actuator. This work presents results for the nonlinear identification of ionic polymer actuator systems driven at a specific frequency. Identification results using a 5th-degree Volterra expansion show that the nonlinear distortion can be accurately modeled. Using such a high power in the series expansion is necessary to capture the most dominant harmonics, as evidenced when examining the power spectral density of the response. An investigation of how nonlinearities enter into the response is also performed. By analyzing both the actuation current and tip velocity, results show that both the voltage to current and current to velocity stages influence the nonlinear response, but the voltage to current stage is more dominantly nonlinear.

  12. Adaptive hybrid intelligent control for uncertain nonlinear dynamical systems.

    PubMed

    Wang, Chi-Hsu; Lin, Tsung-Chih; Lee, Tsu-Tian; Liu, Han-Leih

    2002-01-01

    A new hybrid direct/indirect adaptive fuzzy neural network (FNN) controller with a state observer and supervisory controller for a class of uncertain nonlinear dynamic systems is developed in this paper. The hybrid adaptive FNN controller, the free parameters of which can be tuned on-line by an observer-based output feedback control law and adaptive law, is a combination of direct and indirect adaptive FNN controllers. A weighting factor, which can be adjusted by the tradeoff between plant knowledge and control knowledge, is adopted to sum together the control efforts from indirect adaptive FNN controller and direct adaptive FNN controller. Furthermore, a supervisory controller is appended into the FNN controller to force the state to be within the constraint set. Therefore, if the FNN controller cannot maintain the stability, the supervisory controller starts working to guarantee stability. On the other hand, if the FNN controller works well, the supervisory controller will be deactivated. The overall adaptive scheme guarantees the global stability of the resulting closed-loop system in the sense that all signals involved are uniformly bounded. Two nonlinear systems, namely, inverted pendulum system and Chua's (1989) chaotic circuit, are fully illustrated to track sinusoidal signals. The resulting hybrid direct/indirect FNN control systems show better performances, i.e., tracking error and control effort can be made smaller and it is more flexible during the design process.

  13. The AdaptiV Approach to Verification of Adaptive Systems

    SciTech Connect

    Rouff, Christopher; Buskens, Richard; Pullum, Laura L; Cui, Xiaohui; Hinchey, Mike

    2012-01-01

    Adaptive systems are critical for future space and other unmanned and intelligent systems. Verification of these systems is also critical for their use in systems with potential harm to human life or with large financial investments. Due to their nondeterministic nature and extremely large state space, current methods for verification of software systems are not adequate to provide a high level of assurance. The combination of stabilization science, high performance computing simulations, compositional verification and traditional verification techniques, plus operational monitors, provides a complete approach to verification and deployment of adaptive systems that has not been used before. This paper gives an overview of this approach.

  14. Fractional System Identification: An Approach Using Continuous Order-Distributions

    NASA Technical Reports Server (NTRS)

    Hartley, Tom T.; Lorenzo, Carl F.

    1999-01-01

    This paper discusses the identification of fractional- and integer-order systems using the concept of continuous order-distribution. Based on the ability to define systems using continuous order-distributions, it is shown that frequency domain system identification can be performed using least squares techniques after discretizing the order-distribution.

  15. Computerized Adaptive Testing System Design: Preliminary Design Considerations.

    ERIC Educational Resources Information Center

    Croll, Paul R.

    A functional design model for a computerized adaptive testing (CAT) system was developed and presented through a series of hierarchy plus input-process-output (HIPO) diagrams. System functions were translated into system structure: specifically, into 34 software components. Implementation of the design in a physical system was addressed through…

  16. RASCAL: A Rudimentary Adaptive System for Computer-Aided Learning.

    ERIC Educational Resources Information Center

    Stewart, John Christopher

    Both the background of computer-assisted instruction (CAI) systems in general and the requirements of a computer-aided learning system which would be a reasonable assistant to a teacher are discussed. RASCAL (Rudimentary Adaptive System for Computer-Aided Learning) is a first attempt at defining a CAI system which would individualize the learning…

  17. ERP and Adaptive Autoregressive identification with spectral power decomposition to study rapid auditory processing in infants.

    PubMed

    Piazza, C; Cantiani, C; Tacchino, G; Molteni, M; Reni, G; Bianchi, A M

    2014-01-01

    The ability to process rapidly-occurring auditory stimuli plays an important role in the mechanisms of language acquisition. For this reason, the research community has begun to investigate infant auditory processing, particularly using the Event Related Potentials (ERP) technique. In this paper we approach this issue by means of time domain and time-frequency domain analysis. For the latter, we propose the use of Adaptive Autoregressive (AAR) identification with spectral power decomposition. Results show EEG delta-theta oscillation enhancement related to the processing of acoustic frequency and duration changes, suggesting that, as expected, power modulation encodes rapid auditory processing (RAP) in infants and that the time-frequency analysis method proposed is able to identify this modulation.

  18. Thermal Signature Identification System (TheSIS)

    NASA Technical Reports Server (NTRS)

    Merritt, Scott; Bean, Brian

    2015-01-01

    We characterize both nonlinear and high order linear responses of fiber-optic and optoelectronic components using spread spectrum temperature cycling methods. This Thermal Signature Identification System (TheSIS) provides much more detail than conventional narrowband or quasi-static temperature profiling methods. This detail allows us to match components more thoroughly, detect subtle reversible shifts in performance, and investigate the cause of instabilities or irreversible changes. In particular, we create parameterized models of athermal fiber Bragg gratings (FBGs), delay line interferometers (DLIs), and distributed feedback (DFB) lasers, then subject the alternative models to selection via the Akaike Information Criterion (AIC). Detailed pairing of components, e.g. FBGs, is accomplished by means of weighted distance metrics or norms, rather than on the basis of a single parameter, such as center wavelength.

  19. Computational issue in the analysis of adaptive control systems

    NASA Technical Reports Server (NTRS)

    Kosut, Robert L.

    1989-01-01

    Adaptive systems under slow parameter adaption can be analyzed by the method of averaging. This provides a means to assess stability (and instability) properties of most adaptive systems, either continuous-time or (more importantly for practice) discrete-time, as well as providing an estimate of the region of attraction. Although the method of averaging is conceptually straightforward, even simple examples are well beyond hand calculations. Specific software tools are proposed which can provide the basis for user-friendly environment to perform the necessary computations involved in the averaging analysis.

  20. Advanced Techniques for Power System Identification from Measured Data

    SciTech Connect

    Pierre, John W.; Wies, Richard; Trudnowski, Daniel

    2008-11-25

    Time-synchronized measurements provide rich information for estimating a power-system's electromechanical modal properties via advanced signal processing. This information is becoming critical for the improved operational reliability of interconnected grids. A given mode's properties are described by its frequency, damping, and shape. Modal frequencies and damping are useful indicators of power-system stress, usually declining with increased load or reduced grid capacity. Mode shape provides critical information for operational control actions. This project investigated many advanced techniques for power system identification from measured data focusing on mode frequency and damping ratio estimation. Investigators from the three universities coordinated their effort with Pacific Northwest National Laboratory (PNNL). Significant progress was made on developing appropriate techniques for system identification with confidence intervals and testing those techniques on field measured data and through simulation. Experimental data from the western area power system was provided by PNNL and Bonneville Power Administration (BPA) for both ambient conditions and for signal injection tests. Three large-scale tests were conducted for the western area in 2005 and 2006. Measured field PMU (Phasor Measurement Unit) data was provided to the three universities. A 19-machine simulation model was enhanced for testing the system identification algorithms. Extensive simulations were run with this model to test the performance of the algorithms. University of Wyoming researchers participated in four primary activities: (1) Block and adaptive processing techniques for mode estimation from ambient signals and probing signals, (2) confidence interval estimation, (3) probing signal design and injection method analysis, and (4) performance assessment and validation from simulated and field measured data. Subspace based methods have been use to improve previous results from block processing

  1. Adaptive Mesh Refinement and Adaptive Time Integration for Electrical Wave Propagation on the Purkinje System.

    PubMed

    Ying, Wenjun; Henriquez, Craig S

    2015-01-01

    A both space and time adaptive algorithm is presented for simulating electrical wave propagation in the Purkinje system of the heart. The equations governing the distribution of electric potential over the system are solved in time with the method of lines. At each timestep, by an operator splitting technique, the space-dependent but linear diffusion part and the nonlinear but space-independent reactions part in the partial differential equations are integrated separately with implicit schemes, which have better stability and allow larger timesteps than explicit ones. The linear diffusion equation on each edge of the system is spatially discretized with the continuous piecewise linear finite element method. The adaptive algorithm can automatically recognize when and where the electrical wave starts to leave or enter the computational domain due to external current/voltage stimulation, self-excitation, or local change of membrane properties. Numerical examples demonstrating efficiency and accuracy of the adaptive algorithm are presented.

  2. Adaptive Mesh Refinement and Adaptive Time Integration for Electrical Wave Propagation on the Purkinje System

    PubMed Central

    Ying, Wenjun; Henriquez, Craig S.

    2015-01-01

    A both space and time adaptive algorithm is presented for simulating electrical wave propagation in the Purkinje system of the heart. The equations governing the distribution of electric potential over the system are solved in time with the method of lines. At each timestep, by an operator splitting technique, the space-dependent but linear diffusion part and the nonlinear but space-independent reactions part in the partial differential equations are integrated separately with implicit schemes, which have better stability and allow larger timesteps than explicit ones. The linear diffusion equation on each edge of the system is spatially discretized with the continuous piecewise linear finite element method. The adaptive algorithm can automatically recognize when and where the electrical wave starts to leave or enter the computational domain due to external current/voltage stimulation, self-excitation, or local change of membrane properties. Numerical examples demonstrating efficiency and accuracy of the adaptive algorithm are presented. PMID:26581455

  3. Finite-time master-slave synchronization and parameter identification for uncertain Lurie systems.

    PubMed

    Wang, Tianbo; Zhao, Shouwei; Zhou, Wuneng; Yu, Weiqin

    2014-07-01

    This paper investigates the finite-time master-slave synchronization and parameter identification problem for uncertain Lurie systems based on the finite-time stability theory and the adaptive control method. The finite-time master-slave synchronization means that the state of a slave system follows with that of a master system in finite time, which is more reasonable than the asymptotical synchronization in applications. The uncertainties include the unknown parameters and noise disturbances. An adaptive controller and update laws which ensures the synchronization and parameter identification to be realized in finite time are constructed. Finally, two numerical examples are given to show the effectiveness of the proposed method. PMID:24785822

  4. Design of an adaptive neural network based power system stabilizer.

    PubMed

    Liu, Wenxin; Venayagamoorthy, Ganesh K; Wunsch, Donald C

    2003-01-01

    Power system stabilizers (PSS) are used to generate supplementary control signals for the excitation system in order to damp the low frequency power system oscillations. To overcome the drawbacks of conventional PSS (CPSS), numerous techniques have been proposed in the literature. Based on the analysis of existing techniques, this paper presents an indirect adaptive neural network based power system stabilizer (IDNC) design. The proposed IDNC consists of a neuro-controller, which is used to generate a supplementary control signal to the excitation system, and a neuro-identifier, which is used to model the dynamics of the power system and to adapt the neuro-controller parameters. The proposed method has the features of a simple structure, adaptivity and fast response. The proposed IDNC is evaluated on a single machine infinite bus power system under different operating conditions and disturbances to demonstrate its effectiveness and robustness. PMID:12850048

  5. Detection of Anthropogenic Particles in Fish Stomachs: An Isolation Method Adapted to Identification by Raman Spectroscopy.

    PubMed

    Collard, France; Gilbert, Bernard; Eppe, Gauthier; Parmentier, Eric; Das, Krishna

    2015-10-01

    Microplastic particles (MP) contaminate oceans and affect marine organisms in several ways. Ingestion combined with food intake is generally reported. However, data interpretation often is circumvented by the difficulty to separate MP from bulk samples. Visual examination often is used as one or the only step to sort these particles. However, color, size, and shape are insufficient and often unreliable criteria. We present an extraction method based on hypochlorite digestion and isolation of MP from the membrane by sonication. The protocol is especially well adapted to a subsequent analysis by Raman spectroscopy. The method avoids fluorescence problems, allowing better identification of anthropogenic particles (AP) from stomach contents of fish by Raman spectroscopy. It was developed with commercial samples of microplastics and cotton along with stomach contents from three different Clupeiformes fishes: Clupea harengus, Sardina pilchardus, and Engraulis encrasicolus. The optimized digestion and isolation protocol showed no visible impact on microplastics and cotton particles while the Raman spectroscopic spectrum allowed the precise identification of microplastics and textile fibers. Thirty-five particles were isolated from nine fish stomach contents. Raman analysis has confirmed 11 microplastics and 13 fibers mainly made of cellulose or lignin. Some particles were not completely identified but contained artificial dyes. The novel approach developed in this manuscript should help to assess the presence, quantity, and composition of AP in planktivorous fish stomachs. PMID:26289815

  6. Clustering of tethered satellite system simulation data by an adaptive neuro-fuzzy algorithm

    NASA Technical Reports Server (NTRS)

    Mitra, Sunanda; Pemmaraju, Surya

    1992-01-01

    Recent developments in neuro-fuzzy systems indicate that the concepts of adaptive pattern recognition, when used to identify appropriate control actions corresponding to clusters of patterns representing system states in dynamic nonlinear control systems, may result in innovative designs. A modular, unsupervised neural network architecture, in which fuzzy learning rules have been embedded is used for on-line identification of similar states. The architecture and control rules involved in Adaptive Fuzzy Leader Clustering (AFLC) allow this system to be incorporated in control systems for identification of system states corresponding to specific control actions. We have used this algorithm to cluster the simulation data of Tethered Satellite System (TSS) to estimate the range of delta voltages necessary to maintain the desired length rate of the tether. The AFLC algorithm is capable of on-line estimation of the appropriate control voltages from the corresponding length error and length rate error without a priori knowledge of their membership functions and familarity with the behavior of the Tethered Satellite System.

  7. Optimizing Input/Output Using Adaptive File System Policies

    NASA Technical Reports Server (NTRS)

    Madhyastha, Tara M.; Elford, Christopher L.; Reed, Daniel A.

    1996-01-01

    Parallel input/output characterization studies and experiments with flexible resource management algorithms indicate that adaptivity is crucial to file system performance. In this paper we propose an automatic technique for selecting and refining file system policies based on application access patterns and execution environment. An automatic classification framework allows the file system to select appropriate caching and pre-fetching policies, while performance sensors provide feedback used to tune policy parameters for specific system environments. To illustrate the potential performance improvements possible using adaptive file system policies, we present results from experiments involving classification-based and performance-based steering.

  8. Identification of the Unstable Human Postural Control System

    PubMed Central

    Hwang, Sungjae; Agada, Peter; Kiemel, Tim; Jeka, John J.

    2016-01-01

    Maintaining upright bipedal posture requires a control system that continually adapts to changing environmental conditions, such as different support surfaces. Behavioral changes associated with different support surfaces, such as the predominance of an ankle or hip strategy, is considered to reflect a change in the control strategy. However, tracing such behavioral changes to a specific component in a closed loop control system is challenging. Here we used the joint input–output (JIO) method of closed-loop system identification to identify the musculoskeletal and neural feedback components of the human postural control loop. The goal was to establish changes in the control loop corresponding to behavioral changes observed on different support surfaces. Subjects were simultaneously perturbed by two independent mechanical and two independent sensory perturbations while standing on a normal or short support surface. The results show a dramatic phase reversal between visual input and body kinematics due to the change in surface condition from trunk leads legs to legs lead trunk with increasing frequency of the visual perturbation. Through decomposition of the control loop, we found that behavioral change is not necessarily due to a change in control strategy, but in the case of different support surfaces, is linked to changes in properties of the plant. The JIO method is an important tool to identify the contribution of specific components within a closed loop control system to overall postural behavior and may be useful to devise better treatment of balance disorders. PMID:27013990

  9. The immune system, adaptation, and machine learning

    NASA Astrophysics Data System (ADS)

    Farmer, J. Doyne; Packard, Norman H.; Perelson, Alan S.

    1986-10-01

    The immune system is capable of learning, memory, and pattern recognition. By employing genetic operators on a time scale fast enough to observe experimentally, the immune system is able to recognize novel shapes without preprogramming. Here we describe a dynamical model for the immune system that is based on the network hypothesis of Jerne, and is simple enough to simulate on a computer. This model has a strong similarity to an approach to learning and artificial intelligence introduced by Holland, called the classifier system. We demonstrate that simple versions of the classifier system can be cast as a nonlinear dynamical system, and explore the analogy between the immune and classifier systems in detail. Through this comparison we hope to gain insight into the way they perform specific tasks, and to suggest new approaches that might be of value in learning systems.

  10. Lightweight autonomous chemical identification system (LACIS)

    NASA Astrophysics Data System (ADS)

    Lozos, George; Lin, Hai; Burch, Timothy

    2012-06-01

    Smiths Detection and Intelligent Optical Systems have developed prototypes for the Lightweight Autonomous Chemical Identification System (LACIS) for the US Department of Homeland Security. LACIS is to be a handheld detection system for Chemical Warfare Agents (CWAs) and Toxic Industrial Chemicals (TICs). LACIS is designed to have a low limit of detection and rapid response time for use by emergency responders and could allow determination of areas having dangerous concentration levels and if protective garments will be required. Procedures for protection of responders from hazardous materials incidents require the use of protective equipment until such time as the hazard can be assessed. Such accurate analysis can accelerate operations and increase effectiveness. LACIS is to be an improved point detector employing novel CBRNE detection modalities that includes a militaryproven ruggedized ion mobility spectrometer (IMS) with an array of electro-resistive sensors to extend the range of chemical threats detected in a single device. It uses a novel sensor data fusion and threat classification architecture to interpret the independent sensor responses and provide robust detection at low levels in complex backgrounds with minimal false alarms. The performance of LACIS prototypes have been characterized in independent third party laboratory tests at the Battelle Memorial Institute (BMI, Columbus, OH) and indoor and outdoor field tests at the Nevada National Security Site (NNSS). LACIS prototypes will be entering operational assessment by key government emergency response groups to determine its capabilities versus requirements.

  11. Design of a Performance-Adaptive PID Control System Based on Modeling Performance Assessment

    NASA Astrophysics Data System (ADS)

    Yamamoto, Toru

    In industrial processes represented by petroleum and refinery processes, it is necessary to establish the performance-driven control strategy in order to improve the productivity, which the control performance is firstly evaluated, and the controller is reconstructed. This paper describes a design scheme of performance-adaptive PID controllers which are based on the above control mechanism. According to the proposed control scheme, the system identification works corresponding to the result of modeling performance assessment, and PID parameters are computed using the newly estimated system parameters. In calculating the PID parameters, the desired control performance is considered. The behaviour of the proposed control scheme is numerically examined in some simulation examples.

  12. Adaptive Neural Network Based Control of Noncanonical Nonlinear Systems.

    PubMed

    Zhang, Yanjun; Tao, Gang; Chen, Mou

    2016-09-01

    This paper presents a new study on the adaptive neural network-based control of a class of noncanonical nonlinear systems with large parametric uncertainties. Unlike commonly studied canonical form nonlinear systems whose neural network approximation system models have explicit relative degree structures, which can directly be used to derive parameterized controllers for adaptation, noncanonical form nonlinear systems usually do not have explicit relative degrees, and thus their approximation system models are also in noncanonical forms. It is well-known that the adaptive control of noncanonical form nonlinear systems involves the parameterization of system dynamics. As demonstrated in this paper, it is also the case for noncanonical neural network approximation system models. Effective control of such systems is an open research problem, especially in the presence of uncertain parameters. This paper shows that it is necessary to reparameterize such neural network system models for adaptive control design, and that such reparameterization can be realized using a relative degree formulation, a concept yet to be studied for general neural network system models. This paper then derives the parameterized controllers that guarantee closed-loop stability and asymptotic output tracking for noncanonical form neural network system models. An illustrative example is presented with the simulation results to demonstrate the control design procedure, and to verify the effectiveness of such a new design method.

  13. Adaptive Fuzzy Systems in Computational Intelligence

    NASA Technical Reports Server (NTRS)

    Berenji, Hamid R.

    1996-01-01

    In recent years, the interest in computational intelligence techniques, which currently includes neural networks, fuzzy systems, and evolutionary programming, has grown significantly and a number of their applications have been developed in the government and industry. In future, an essential element in these systems will be fuzzy systems that can learn from experience by using neural network in refining their performances. The GARIC architecture, introduced earlier, is an example of a fuzzy reinforcement learning system which has been applied in several control domains such as cart-pole balancing, simulation of to Space Shuttle orbital operations, and tether control. A number of examples from GARIC's applications in these domains will be demonstrated.

  14. Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors.

    PubMed

    Villaverde, Monica; Perez, David; Moreno, Felix

    2015-01-01

    The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor's infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc. PMID:26593920

  15. Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors

    PubMed Central

    Villaverde, Monica; Perez, David; Moreno, Felix

    2015-01-01

    The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor’s infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc. PMID:26593920

  16. Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors.

    PubMed

    Villaverde, Monica; Perez, David; Moreno, Felix

    2015-11-17

    The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor's infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.

  17. Recent developments in learning control and system identification for robots and structures

    NASA Technical Reports Server (NTRS)

    Phan, M.; Juang, J.-N.; Longman, R. W.

    1990-01-01

    This paper reviews recent results in learning control and learning system identification, with particular emphasis on discrete-time formulation, and their relation to adaptive theory. Related continuous-time results are also discussed. Among the topics presented are proportional, derivative, and integral learning controllers, time-domain formulation of discrete learning algorithms. Newly developed techniques are described including the concept of the repetition domain, and the repetition domain formulation of learning control by linear feedback, model reference learning control, indirect learning control with parameter estimation, as well as related basic concepts, recursive and non-recursive methods for learning identification.

  18. Communication system with adaptive noise suppression

    NASA Technical Reports Server (NTRS)

    Kozel, David (Inventor); Devault, James A. (Inventor); Birr, Richard B. (Inventor)

    2007-01-01

    A signal-to-noise ratio dependent adaptive spectral subtraction process eliminates noise from noise-corrupted speech signals. The process first pre-emphasizes the frequency components of the input sound signal which contain the consonant information in human speech. Next, a signal-to-noise ratio is determined and a spectral subtraction proportion adjusted appropriately. After spectral subtraction, low amplitude signals can be squelched. A single microphone is used to obtain both the noise-corrupted speech and the average noise estimate. This is done by determining if the frame of data being sampled is a voiced or unvoiced frame. During unvoiced frames an estimate of the noise is obtained. A running average of the noise is used to approximate the expected value of the noise. Spectral subtraction may be performed on a composite noise-corrupted signal, or upon individual sub-bands of the noise-corrupted signal. Pre-averaging of the input signal's magnitude spectrum over multiple time frames may be performed to reduce musical noise.

  19. Adaptive control of Hammerstein-Wiener nonlinear systems

    NASA Astrophysics Data System (ADS)

    Zhang, Bi; Hong, Hyokchan; Mao, Zhizhong

    2016-07-01

    The Hammerstein-Wiener model is a block-oriented model, having a linear dynamic block sandwiched by two static nonlinear blocks. This note develops an adaptive controller for a special form of Hammerstein-Wiener nonlinear systems which are parameterized by the key-term separation principle. The adaptive control law and recursive parameter estimation are updated by the use of internal variable estimations. By modeling the errors due to the estimation of internal variables, we establish convergence and stability properties. Theoretical results show that parameter estimation convergence and closed-loop system stability can be guaranteed under sufficient condition. From a qualitative analysis of the sufficient condition, we introduce an adaptive weighted factor to improve the performance of the adaptive controller. Numerical examples are given to confirm the results in this paper.

  20. Screening systems adapt to changing conditions

    SciTech Connect

    Fiscor, S.

    2009-08-15

    Prep plants are installing larger screening systems and synthetic media is meeting those challenges. The largest manufacturer of synthetic screen media is Polydeck located in Spartanburg, South Carolina. The company's primary product lines include modular polyurethane and rubber screen panels and the frame systems to support the media. The modular approach overcomes a wear problem in one area of the deck common on Banana screens and facilitates maintenance. A rubber formation used in 1- x 2-pt screen panels called the Flexi design is softer and allows more vibration than standard urethane panels. The Maxi screen panel design combined with the PipeTop II frame makes the system highly versatile. 1 photo.

  1. Distributed adaptive simulation through standards-based integration of simulators and adaptive learning systems.

    PubMed

    Bergeron, Bryan; Cline, Andrew; Shipley, Jaime

    2012-01-01

    We have developed a distributed, standards-based architecture that enables simulation and simulator designers to leverage adaptive learning systems. Our approach, which incorporates an electronic competency record, open source LMS, and open source microcontroller hardware, is a low-cost, pragmatic option to integrating simulators with traditional courseware. PMID:22356955

  2. 49 CFR 1542.211 - Identification systems.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... secured area or SIDA continuously displays the identification medium issued to that individual on the... individual who has authorized unescorted access to secured areas and SIDA's to ascertain the authority of any... approved identification media. The procedure must— (1) Apply uniformly in secured areas, SIDAs,...

  3. 49 CFR 1542.211 - Identification systems.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... secured area or SIDA continuously displays the identification medium issued to that individual on the... individual who has authorized unescorted access to secured areas and SIDA's to ascertain the authority of any... approved identification media. The procedure must— (1) Apply uniformly in secured areas, SIDAs,...

  4. Adaptive sliding mode control for a class of chaotic systems

    SciTech Connect

    Farid, R.; Ibrahim, A.; Zalam, B.

    2015-03-30

    Chaos control here means to design a controller that is able to mitigating or eliminating the chaos behavior of nonlinear systems that experiencing such phenomenon. In this paper, an Adaptive Sliding Mode Controller (ASMC) is presented based on Lyapunov stability theory. The well known Chua's circuit is chosen to be our case study in this paper. The study shows the effectiveness of the proposed adaptive sliding mode controller.

  5. Identification of robust adaptation gene regulatory network parameters using an improved particle swarm optimization algorithm.

    PubMed

    Huang, X N; Ren, H P

    2016-01-01

    Robust adaptation is a critical ability of gene regulatory network (GRN) to survive in a fluctuating environment, which represents the system responding to an input stimulus rapidly and then returning to its pre-stimulus steady state timely. In this paper, the GRN is modeled using the Michaelis-Menten rate equations, which are highly nonlinear differential equations containing 12 undetermined parameters. The robust adaption is quantitatively described by two conflicting indices. To identify the parameter sets in order to confer the GRNs with robust adaptation is a multi-variable, multi-objective, and multi-peak optimization problem, which is difficult to acquire satisfactory solutions especially high-quality solutions. A new best-neighbor particle swarm optimization algorithm is proposed to implement this task. The proposed algorithm employs a Latin hypercube sampling method to generate the initial population. The particle crossover operation and elitist preservation strategy are also used in the proposed algorithm. The simulation results revealed that the proposed algorithm could identify multiple solutions in one time running. Moreover, it demonstrated a superior performance as compared to the previous methods in the sense of detecting more high-quality solutions within an acceptable time. The proposed methodology, owing to its universality and simplicity, is useful for providing the guidance to design GRN with superior robust adaptation. PMID:27323043

  6. An adaptive learning control system for aircraft

    NASA Technical Reports Server (NTRS)

    Mekel, R.; Nachmias, S.

    1978-01-01

    A learning control system and its utilization as a flight control system for F-8 Digital Fly-By-Wire (DFBW) research aircraft is studied. The system has the ability to adjust a gain schedule to account for changing plant characteristics and to improve its performance and the plant's performance in the course of its own operation. Three subsystems are detailed: (1) the information acquisition subsystem which identifies the plant's parameters at a given operating condition; (2) the learning algorithm subsystem which relates the identified parameters to predetermined analytical expressions describing the behavior of the parameters over a range of operating conditions; and (3) the memory and control process subsystem which consists of the collection of updated coefficients (memory) and the derived control laws. Simulation experiments indicate that the learning control system is effective in compensating for parameter variations caused by changes in flight conditions.

  7. CRISPR-Based Adaptive Immune Systems

    PubMed Central

    Terns, Michael P.; Terns, Rebecca M.

    2011-01-01

    CRISPR-Cas systems are recently discovered, RNA-based immune systems that control invasions of viruses and plasmids in archaea and bacteria. Prokaryotes with CRISPR-Cas immune systems capture short invader sequences within the CRISPR loci in their genomes, and small RNAs produced from the CRISPR loci (CRISPR (cr)RNAs) guide Cas proteins to recognize and degrade (or otherwise silence) the invading nucleic acids. There are multiple variations of the pathway found among prokaryotes, each mediated by largely distinct components and mechanisms that we are only beginning to delineate. Here we will review our current understanding of the remarkable CRISPR-Cas pathways with particular attention to studies relevant to systems found in the archaea. PMID:21531607

  8. Synthesis of oscillating adaptive feedback systems

    NASA Technical Reports Server (NTRS)

    Smay, J. W.

    1973-01-01

    A synthesis theory is developed which allows system design to proceed from practical specifications on system command and/or disturbance response to a design which is very nearly optimal in terms of feedback sensor noise effects. The approach taken is to replace the nonlinear element by a mean square error minimizing approximation (dual-input describing function), and then use linear frequency domain synthesis techniques subject to additional constraints imposed by the limit cycle and the approximator. Synthesis techniques are also developed for a similar system using an externally excited oscillating signal with the above approach. The results remove the design of the systems considered from the realm of simulation and experimentation, permitting true synthesis and the optimization that accompanies it.

  9. System identification and model reduction using modulating function techniques

    NASA Technical Reports Server (NTRS)

    Shen, Yan

    1993-01-01

    Weighted least squares (WLS) and adaptive weighted least squares (AWLS) algorithms are initiated for continuous-time system identification using Fourier type modulating function techniques. Two stochastic signal models are examined using the mean square properties of the stochastic calculus: an equation error signal model with white noise residuals, and a more realistic white measurement noise signal model. The covariance matrices in each model are shown to be banded and sparse, and a joint likelihood cost function is developed which links the real and imaginary parts of the modulated quantities. The superior performance of above algorithms is demonstrated by comparing them with the LS/MFT and popular predicting error method (PEM) through 200 Monte Carlo simulations. A model reduction problem is formulated with the AWLS/MFT algorithm, and comparisons are made via six examples with a variety of model reduction techniques, including the well-known balanced realization method. Here the AWLS/MFT algorithm manifests higher accuracy in almost all cases, and exhibits its unique flexibility and versatility. Armed with this model reduction, the AWLS/MFT algorithm is extended into MIMO transfer function system identification problems. The impact due to the discrepancy in bandwidths and gains among subsystem is explored through five examples. Finally, as a comprehensive application, the stability derivatives of the longitudinal and lateral dynamics of an F-18 aircraft are identified using physical flight data provided by NASA. A pole-constrained SIMO and MIMO AWLS/MFT algorithm is devised and analyzed. Monte Carlo simulations illustrate its high-noise rejecting properties. Utilizing the flight data, comparisons among different MFT algorithms are tabulated and the AWLS is found to be strongly favored in almost all facets.

  10. ADAPTIVE FULL-SPECTRUM SOLOR ENERGY SYSTEMS

    SciTech Connect

    Byard D. Wood

    2004-04-01

    This RD&D project is a three year team effort to develop a hybrid solar lighting (HSL) system that transports solar light from a paraboloidal dish concentrator to a luminaire via a large core polymer fiber optic. The luminaire can be a device to distribute sunlight into a space for the production of algae or it can be a device that is a combination of solar lighting and electric lighting. A benchmark prototype system has been developed to evaluate the HSL system. Sunlight is collected using a one-meter paraboloidal concentrator dish with two-axis tracking. A secondary mirror consisting of eight planar-segmented mirrors directs the visible part of the spectrum to eight fibers (receiver) and subsequently to eight luminaires. This results in about 8,200 lumens incident at each fiber tip. Each fiber can illuminate about 16.7 m{sup 2} (180 ft{sup 2}) of office space. The IR spectrum is directed to a thermophotovoltaic (TPV) array to produce electricity. During this reporting period, the project team made advancements in the design of the second generation (Alpha) system. For the Alpha system, the eight individual 12 mm fibers have been replaced with a centralized bundle of 3 mm fibers. The TRNSYS Full-Spectrum Solar Energy System model has been updated and new components have been added. The TPV array and nonimaging device have been tested and progress has been made in the fiber transmission models. A test plan was developed for both the high-lumen tests and the study to determine the non-energy benefits of daylighting. The photobioreactor team also made major advancements in the testing of model scale and bench top lab-scale systems.

  11. Fast calibration of high-order adaptive optics systems.

    PubMed

    Kasper, Markus; Fedrigo, Enrico; Looze, Douglas P; Bonnet, Henri; Ivanescu, Liviu; Oberti, Sylvain

    2004-06-01

    We present a new method of calibrating adaptive optics systems that greatly reduces the required calibration time or, equivalently, improves the signal-to-noise ratio. The method uses an optimized actuation scheme with Hadamard patterns and does not scale with the number of actuators for a given noise level in the wavefront sensor channels. It is therefore highly desirable for high-order systems and/or adaptive secondary systems on a telescope without a Gregorian focal plane. In the latter case, the measurement noise is increased by the effects of the turbulent atmosphere when one is calibrating on a natural guide star. PMID:15191182

  12. Fast calibration of high-order adaptive optics systems.

    PubMed

    Kasper, Markus; Fedrigo, Enrico; Looze, Douglas P; Bonnet, Henri; Ivanescu, Liviu; Oberti, Sylvain

    2004-06-01

    We present a new method of calibrating adaptive optics systems that greatly reduces the required calibration time or, equivalently, improves the signal-to-noise ratio. The method uses an optimized actuation scheme with Hadamard patterns and does not scale with the number of actuators for a given noise level in the wavefront sensor channels. It is therefore highly desirable for high-order systems and/or adaptive secondary systems on a telescope without a Gregorian focal plane. In the latter case, the measurement noise is increased by the effects of the turbulent atmosphere when one is calibrating on a natural guide star.

  13. Network adaptable information systems for safeguard applications

    SciTech Connect

    Rodriguez, C.; Burczyk, L.; Chare, P.; Wagner, H.

    1996-09-01

    While containment and surveillance systems designed for nuclear safeguards have greatly improved through advances in computer, sensor, and microprocessor technologies, the authors recognize the need to continue the advancement of these systems to provide more standardized solutions for safeguards applications of the future. The benefits to be gained from the use of standardized technologies are becoming evident as safeguard activities are increasing world-wide while funding of these activities is becoming more limited. The EURATOM Safeguards Directorate and Los Alamos National Laboratory are developing and testing advanced monitoring technologies coupled with the most efficient solutions for the safeguards applications of the future.

  14. Adaptation In Biological Sensory-Motor Systems: A Model For Robotic Control.

    NASA Astrophysics Data System (ADS)

    Mukerjee, Amitabha

    1985-01-01

    Biological sensory-motor systems have an extraordinary facility for adaptation. The accurate behavior demonstrated by such systems even under severe informational discrepancy has generated theories proposing altered internal models as the basis for such adaptation. Here we propose a similar perturbed parameter scheme for the low-level control of robotic manipulators. Thus, the dynamic and kinematic parameters in any suitable theoretical model can be perturbed from their true values in order to achieve enhanced performance in the vicinity of a given trajectory. Critical issues in this approach involve selection of parameters for identification and the estimation technique itself. A new approach is also highlighted which permits the self-calibration of the link inertias while executing any desired trajectory.

  15. Adaptive Device Context Based Mobile Learning Systems

    ERIC Educational Resources Information Center

    Pu, Haitao; Lin, Jinjiao; Song, Yanwei; Liu, Fasheng

    2011-01-01

    Mobile learning is e-learning delivered through mobile computing devices, which represents the next stage of computer-aided, multi-media based learning. Therefore, mobile learning is transforming the way of traditional education. However, as most current e-learning systems and their contents are not suitable for mobile devices, an approach for…

  16. A Model of Internal Communication in Adaptive Communication Systems.

    ERIC Educational Resources Information Center

    Williams, M. Lee

    A study identified and categorized different types of internal communication systems and developed an applied model of internal communication in adaptive organizational systems. Twenty-one large organizations were selected for their varied missions and diverse approaches to managing internal communication. Individual face-to-face or telephone…

  17. Integrating Learning Styles into Adaptive E-Learning System

    ERIC Educational Resources Information Center

    Truong, Huong May

    2015-01-01

    This paper provides an overview and update on my PhD research project which focuses on integrating learning styles into adaptive e-learning system. The project, firstly, aims to develop a system to classify students' learning styles through their online learning behaviour. This will be followed by a study on the complex relationship between…

  18. Autonomous system for pathogen detection and identification

    SciTech Connect

    Belgrader, P.; Benett, W.; Bergman, W.; Langlois, R.; Mariella, R.; Milanovich, F.; Miles, R.; Venkateswaran, K.; Long, G.; Nelson, W.

    1998-09-24

    This purpose of this project is to build a prototype instrument that will, running unattended, detect, identify, and quantify BW agents. In order to accomplish this, we have chosen to start with the world' s leading, proven, assays for pathogens: surface-molecular recognition assays, such as antibody-based assays, implemented on a high-performance, identification (ID)-capable flow cytometer, and the polymerase chain reaction (PCR) for nucleic-acid based assays. With these assays, we must integrate the capability to: l collect samples from aerosols, water, or surfaces; l perform sample preparation prior to the assays; l incubate the prepared samples, if necessary, for a period of time; l transport the prepared, incubated samples to the assays; l perform the assays; l interpret and report the results of the assays. Issues such as reliability, sensitivity and accuracy, quantity of consumables, maintenance schedule, etc. must be addressed satisfactorily to the end user. The highest possible sensitivity and specificity of the assay must be combined with no false alarms. Today, we have assays that can, in under 30 minutes, detect and identify simulants for BW agents at concentrations of a few hundred colony-forming units per ml of solution. If the bio-aerosol sampler of this system collects 1000 Ymin and concentrates the respirable particles into 1 ml of solution with 70% processing efficiency over a period of 5 minutes, then this translates to a detection/ID capability of under 0.1 agent-containing particle/liter of air.

  19. Neural system prediction and identification challenge

    PubMed Central

    Vlachos, Ioannis; Zaytsev, Yury V.; Spreizer, Sebastian; Aertsen, Ad; Kumar, Arvind

    2013-01-01

    Can we infer the function of a biological neural network (BNN) if we know the connectivity and activity of all its constituent neurons?This question is at the core of neuroscience and, accordingly, various methods have been developed to record the activity and connectivity of as many neurons as possible. Surprisingly, there is no theoretical or computational demonstration that neuronal activity and connectivity are indeed sufficient to infer the function of a BNN. Therefore, we pose the Neural Systems Identification and Prediction Challenge (nuSPIC). We provide the connectivity and activity of all neurons and invite participants (1) to infer the functions implemented (hard-wired) in spiking neural networks (SNNs) by stimulating and recording the activity of neurons and, (2) to implement predefined mathematical/biological functions using SNNs. The nuSPICs can be accessed via a web-interface to the NEST simulator and the user is not required to know any specific programming language. Furthermore, the nuSPICs can be used as a teaching tool. Finally, nuSPICs use the crowd-sourcing model to address scientific issues. With this computational approach we aim to identify which functions can be inferred by systematic recordings of neuronal activity and connectivity. In addition, nuSPICs will help the design and application of new experimental paradigms based on the structure of the SNN and the presumed function which is to be discovered. PMID:24399966

  20. Decentralized system identification using stochastic subspace identification for wireless sensor networks.

    PubMed

    Cho, Soojin; Park, Jong-Woong; Sim, Sung-Han

    2015-04-08

    Wireless sensor networks (WSNs) facilitate a new paradigm to structural identification and monitoring for civil infrastructure. Conventional structural monitoring systems based on wired sensors and centralized data acquisition systems are costly for installation as well as maintenance. WSNs have emerged as a technology that can overcome such difficulties, making deployment of a dense array of sensors on large civil structures both feasible and economical. However, as opposed to wired sensor networks in which centralized data acquisition and processing is common practice, WSNs require decentralized computing algorithms to reduce data transmission due to the limitation associated with wireless communication. In this paper, the stochastic subspace identification (SSI) technique is selected for system identification, and SSI-based decentralized system identification (SDSI) is proposed to be implemented in a WSN composed of Imote2 wireless sensors that measure acceleration. The SDSI is tightly scheduled in the hierarchical WSN, and its performance is experimentally verified in a laboratory test using a 5-story shear building model.

  1. Framework for Adaptable Operating and Runtime Systems: Final Project Report

    SciTech Connect

    Patrick G. Bridges

    2012-02-01

    In this grant, we examined a wide range of techniques for constructing high-performance con gurable system software for HPC systems and its application to DOE-relevant problems. Overall, research and development on this project focused in three specifc areas: (1) software frameworks for constructing and deploying con gurable system software, (2) applcation of these frameworks to HPC-oriented adaptable networking software, (3) performance analysis of HPC system software to understand opportunities for performance optimization.

  2. Lessons from Adaptive Level One Accelerator (ALOA) System Implementation

    NASA Technical Reports Server (NTRS)

    Patel, Umesh D.; Brambora, Clifford; Ghuman, Parminder; Day, John H. (Technical Monitor)

    2001-01-01

    The Adaptive Level One Accelerator (ALOA) system was developed as part of the Earth Science Data and Information System (ESDIS) project. The reconfigurable computing technologies were investigated for Level 1 satellite telemetry data processing to achieve computing acceleration and cost reduction for the next-generation Level 1 data processing systems. The MODIS instrument calibration algorithm was implemented using reconfigurable a computer. The system development process and the lessons learned throughout the design cycle are summarized in this paper.

  3. Method and system for environmentally adaptive fault tolerant computing

    NASA Technical Reports Server (NTRS)

    Copenhaver, Jason L. (Inventor); Jeremy, Ramos (Inventor); Wolfe, Jeffrey M. (Inventor); Brenner, Dean (Inventor)

    2010-01-01

    A method and system for adapting fault tolerant computing. The method includes the steps of measuring an environmental condition representative of an environment. An on-board processing system's sensitivity to the measured environmental condition is measured. It is determined whether to reconfigure a fault tolerance of the on-board processing system based in part on the measured environmental condition. The fault tolerance of the on-board processing system may be reconfigured based in part on the measured environmental condition.

  4. Adaptive control with an expert system based supervisory level. Thesis

    NASA Technical Reports Server (NTRS)

    Sullivan, Gerald A.

    1991-01-01

    Adaptive control is presently one of the methods available which may be used to control plants with poorly modelled dynamics or time varying dynamics. Although many variations of adaptive controllers exist, a common characteristic of all adaptive control schemes, is that input/output measurements from the plant are used to adjust a control law in an on-line fashion. Ideally the adjustment mechanism of the adaptive controller is able to learn enough about the dynamics of the plant from input/output measurements to effectively control the plant. In practice, problems such as measurement noise, controller saturation, and incorrect model order, to name a few, may prevent proper adjustment of the controller and poor performance or instability result. In this work we set out to avoid the inadequacies of procedurally implemented safety nets, by introducing a two level control scheme in which an expert system based 'supervisor' at the upper level provides all the safety net functions for an adaptive controller at the lower level. The expert system is based on a shell called IPEX, (Interactive Process EXpert), that we developed specifically for the diagnosis and treatment of dynamic systems. Some of the more important functions that the IPEX system provides are: (1) temporal reasoning; (2) planning of diagnostic activities; and (3) interactive diagnosis. Also, because knowledge and control logic are separate, the incorporation of new diagnostic and treatment knowledge is relatively simple. We note that the flexibility available in the system to express diagnostic and treatment knowledge, allows much greater functionality than could ever be reasonably expected from procedural implementations of safety nets. The remainder of this chapter is divided into three sections. In section 1.1 we give a detailed review of the literature in the area of supervisory systems for adaptive controllers. In particular, we describe the evolution of safety nets from simple ad hoc techniques, up

  5. Effects of adaptive task allocation on monitoring of automated systems

    NASA Technical Reports Server (NTRS)

    Parasuraman, R.; Mouloua, M.; Molloy, R.

    1996-01-01

    The effects of adaptive task allocation on monitoring for automation failure during multitask flight simulation were examined. Participants monitored an automated engine status task while simultaneously performing tracking and fuel management tasks over three 30-min sessions. Two methods of adaptive task allocation, both involving temporary return of the automated engine status task to the human operator ("human control"), were examined as a possible countermeasure to monitoring inefficiency. For the model-based adaptive group, the engine status task was allocated to all participants in the middle of the second session for 10 min, following which it was again returned to automation control. The same occurred for the performance-based adaptive group, but only if an individual participant's monitoring performance up to that point did not meet a specified criterion. For the nonadaptive control groups, the engine status task remained automated throughout the experiment. All groups had low probabilities of detection of automation failures for the first 40 min spent with automation. However, following the 10-min intervening period of human control, both adaptive groups detected significantly more automation failures during the subsequent blocks under automation control. The results show that adaptive task allocation can enhance monitoring of automated systems. Both model-based and performance-based allocation improved monitoring of automation. Implications for the design of automated systems are discussed.

  6. Adaptation in the innate immune system and heterologous innate immunity.

    PubMed

    Martin, Stefan F

    2014-11-01

    The innate immune system recognizes deviation from homeostasis caused by infectious or non-infectious assaults. The threshold for its activation seems to be established by a calibration process that includes sensing of microbial molecular patterns from commensal bacteria and of endogenous signals. It is becoming increasingly clear that adaptive features, a hallmark of the adaptive immune system, can also be identified in the innate immune system. Such adaptations can result in the manifestation of a primed state of immune and tissue cells with a decreased activation threshold. This keeps the system poised to react quickly. Moreover, the fact that the innate immune system recognizes a wide variety of danger signals via pattern recognition receptors that often activate the same signaling pathways allows for heterologous innate immune stimulation. This implies that, for example, the innate immune response to an infection can be modified by co-infections or other innate stimuli. This "design feature" of the innate immune system has many implications for our understanding of individual susceptibility to diseases or responsiveness to therapies and vaccinations. In this article, adaptive features of the innate immune system as well as heterologous innate immunity and their implications are discussed.

  7. An Approach to V&V of Embedded Adaptive Systems

    NASA Technical Reports Server (NTRS)

    Liu, Yan; Yerramalla, Sampath; Fuller, Edgar; Cukic, Bojan; Gururajan, Srikaruth

    2004-01-01

    Rigorous Verification and Validation (V&V) techniques are essential for high assurance systems. Lately, the performance of some of these systems is enhanced by embedded adaptive components in order to cope with environmental changes. Although the ability of adapting is appealing, it actually poses a problem in terms of V&V. Since uncertainties induced by environmental changes have a significant impact on system behavior, the applicability of conventional V&V techniques is limited. In safety-critical applications such as flight control system, the mechanisms of change must be observed, diagnosed, accommodated and well understood prior to deployment. In this paper, we propose a non-conventional V&V approach suitable for online adaptive systems. We apply our approach to an intelligent flight control system that employs a particular type of Neural Networks (NN) as the adaptive learning paradigm. Presented methodology consists of a novelty detection technique and online stability monitoring tools. The novelty detection technique is based on Support Vector Data Description that detects novel (abnormal) data patterns. The Online Stability Monitoring tools based on Lyapunov's Stability Theory detect unstable learning behavior in neural networks. Cases studies based on a high fidelity simulator of NASA's Intelligent Flight Control System demonstrate a successful application of the presented V&V methodology. ,

  8. SDR implementation of the receiver of adaptive communication system

    NASA Astrophysics Data System (ADS)

    Skarzynski, Jacek; Darmetko, Marcin; Kozlowski, Sebastian; Kurek, Krzysztof

    2016-04-01

    The paper presents software implementation of a receiver forming a part of an adaptive communication system. The system is intended for communication with a satellite placed in a low Earth orbit (LEO). The ability of adaptation is believed to increase the total amount of data transmitted from the satellite to the ground station. Depending on the signal-to-noise ratio (SNR) of the received signal, adaptive transmission is realized using different transmission modes, i.e., different modulation schemes (BPSK, QPSK, 8-PSK, and 16-APSK) and different convolutional code rates (1/2, 2/3, 3/4, 5/6, and 7/8). The receiver consists of a software-defined radio (SDR) module (National Instruments USRP-2920) and a multithread reception software running on Windows operating system. In order to increase the speed of signal processing, the software takes advantage of single instruction multiple data instructions supported by x86 processor architecture.

  9. An adaptive brain actuated system for augmenting rehabilitation

    PubMed Central

    Roset, Scott A.; Gant, Katie; Prasad, Abhishek; Sanchez, Justin C.

    2014-01-01

    For people living with paralysis, restoration of hand function remains the top priority because it leads to independence and improvement in quality of life. In approaches to restore hand and arm function, a goal is to better engage voluntary control and counteract maladaptive brain reorganization that results from non-use. Standard rehabilitation augmented with developments from the study of brain-computer interfaces could provide a combined therapy approach for motor cortex rehabilitation and to alleviate motor impairments. In this paper, an adaptive brain-computer interface system intended for application to control a functional electrical stimulation (FES) device is developed as an experimental test bed for augmenting rehabilitation with a brain-computer interface. The system's performance is improved throughout rehabilitation by passive user feedback and reinforcement learning. By continuously adapting to the user's brain activity, similar adaptive systems could be used to support clinical brain-computer interface neurorehabilitation over multiple days. PMID:25565945

  10. [Identification system for Sildenafil in health foods].

    PubMed

    Moriyasu, T; Shigeoka, S; Kishimoto, K; Ishikawa, F; Nakajima, J; Kamimura, H; Yasuda, I

    2001-10-01

    A substantially available identification system for Sildenafil in health foods was established using 3 different analytical methods; i.e. TLC, preparative TLC/MS and HPLC/photo-diode array. Sildenafil in health foods was extracted with ethyl acetate under alkaline conditions as sample solutions for TLC and preparative TLC, and also extracted with 50% methanol and then diluted with solution of HPLC mobile phase for HPLC. The sample solution for TLC was applied to Silica gel 60 F254 plates with chloroform/methanol/28% ammonia (90:1:5, under layer) as mobile phase. Spots were located under UV radiation at 254 nm and 366 nm, and spraying dragendorff reagent. The conditions for preparative TLC were the same as these of TLC method, and samples abtained from preparative TLC were determined by MS with APCI interface, under both positive and negative modes. The HPLC analysis was carried out on a column of Cosmosil 5C18-AR (4.6 mm x 150 mm, 5 microns) with 0.05 mol/l phosphate buffer pH 3.0/acetonitrile(73:27) as mobile phase and the eluate was monitored by a photo-diode array detector. The quantitative analysis was available, when the peak of this sample on HPLC was detected at 290 nm. When this system was applied to commercial health foods, Sildenafil was identified and their contents were 25 mg-45 mg/tablet or bottle. These contents nearly correspond to that in Viagra, 25 mg, 50 mg/tablet. Therefore, there is a fear of side effects for Sildenafil, when it is taken as health foods.

  11. Low-latency adaptive optics system processing electronics

    NASA Astrophysics Data System (ADS)

    Duncan, Terry S.; Voas, Joshua K.; Eager, Robert J.; Newey, Scott C.; Wynia, John L.

    2003-02-01

    Extensive system modeling and analysis clearly shows that system latency is a primary performance driver in closed loop adaptive optical systems. With careful attention to all sensing, processing, and controlling components, system latency can be significantly reduced. Upgrades to the Starfire Optical Range (SOR) 3.5-meter telescope facility adaptive optical system have resulted in a reduction in overall latency from 660 μsec to 297 μsec. Future efforts will reduce the system latency even more to the 170 msec range. The changes improve system bandwidth significantly by reducing the "age" of the correction that is applied to the deformable mirror. Latency reductions have been achieved by increasing the pixel readout pattern and rate on the wavefront sensor, utilizing a new high-speed field programmable gate array (FPGA) based wavefront processor, doubling the processing rate of the real-time reconstructor, and streamlining the operation of the deformable mirror drivers.

  12. Effects of Age and Cognition on a Cross-Cultural Paediatric Adaptation of the Sniffin' Sticks Identification Test

    PubMed Central

    Guerreiro, Marilisa Mantovani; Lees, Andrew John; Warner, Thomas T.

    2015-01-01

    Objectives To study the effects of age and cognition on the performance of children aged 3 to 18 years on a culturally adapted version of the 16 item smell identification test from Sniffin' Sticks (SS16). Methods A series of pilots were conducted on 29 children aged 3 to 18 years old and 23 adults to produce an adapted version of the SS16 suitable for Brazilian children (SS16-Child). A final version was applied to 51 children alongside a picture identification test (PIT-SS16-Child) to access cognitive abilities involved in the smell identification task. In addition 20 adults performed the same tasks as a comparison group. Results The final adapted SS16-Child was applied to 51 children with a mean age of 9.9 years (range 3-18 years, SD=4.25 years), of which 68.3% were girls. There was an independent effect of age (p<0.05) and PIT-SS16-Child (p<0.001) on the performance on the SS16-Child, and older children reached the ceiling for scoring in the cognitive and olfactory test. Pre-school children had difficulties identifying items of the test. Discussion/Conclusions A cross-culturally adapted version of the SS16 can be used to test olfaction in children but interpretation of the results must take age and cognitive abilities into consideration. PMID:26267145

  13. Adaptive mass expulsion attitude control system

    NASA Technical Reports Server (NTRS)

    Rodden, John J. (Inventor); Stevens, Homer D. (Inventor); Carrou, Stephane (Inventor)

    2001-01-01

    An attitude control system and method operative with a thruster controls the attitude of a vehicle carrying the thruster, wherein the thruster has a valve enabling the formation of pulses of expelled gas from a source of compressed gas. Data of the attitude of the vehicle is gathered, wherein the vehicle is located within a force field tending to orient the vehicle in a first attitude different from a desired attitude. The attitude data is evaluated to determine a pattern of values of attitude of the vehicle in response to the gas pulses of the thruster and in response to the force field. The system and the method maintain the attitude within a predetermined band of values of attitude which includes the desired attitude. Computation circuitry establishes an optimal duration of each of the gas pulses based on the pattern of values of attitude, the optimal duration providing for a minimal number of opening and closure operations of the valve. The thruster is operated to provide gas pulses having the optimal duration.

  14. Non-linear system identification in flow-induced vibration

    SciTech Connect

    Spanos, P.D.; Zeldin, B.A.; Lu, R.

    1996-12-31

    The paper introduces a method of identification of non-linear systems encountered in marine engineering applications. The non-linearity is accounted for by a combination of linear subsystems and known zero-memory non-linear transformations; an equivalent linear multi-input-single-output (MISO) system is developed for the identification problem. The unknown transfer functions of the MISO system are identified by assembling a system of linear equations in the frequency domain. This system is solved by performing the Cholesky decomposition of a related matrix. It is shown that the proposed identification method can be interpreted as a {open_quotes}Gram-Schmidt{close_quotes} type of orthogonal decomposition of the input-output quantities of the equivalent MISO system. A numerical example involving the identification of unknown parameters of flow (ocean wave) induced forces on offshore structures elucidates the applicability of the proposed method.

  15. Offline synchronization of data acquisition systems using system identification

    NASA Astrophysics Data System (ADS)

    Maes, K.; Reynders, E.; Rezayat, A.; Roeck, G. De; Lombaert, G.

    2016-10-01

    This paper presents a technique for offline time synchronization of data acquisition systems. The technique can be applied when real-time synchronization of data acquisition systems is impossible or not sufficiently accurate. It allows for accurate synchronization based on the acquired dynamic response of the structure only, without requiring a common response or the use of a trigger signal. The synchronization is performed using the results obtained from system identification, and assumes linear dynamic behavior of the structure and proportional damping of the structural modes. A demonstration for a laboratory experiment on a cantilever steel beam shows that the proposed methodology can be used for accurate time synchronization, resulting in a significant improvement of the accuracy of the identified mode shapes.

  16. Real-time control system for adaptive resonator

    SciTech Connect

    Flath, L; An, J; Brase, J; Hurd, R; Kartz, M; Sawvel, R; Silva, D

    2000-07-24

    Sustained operation of high average power solid-state lasers currently requires an adaptive resonator to produce the optimal beam quality. We describe the architecture of a real-time adaptive control system for correcting intra-cavity aberrations in a heat capacity laser. Image data collected from a wavefront sensor are processed and used to control phase with a high-spatial-resolution deformable mirror. Our controller takes advantage of recent developments in low-cost, high-performance processor technology. A desktop-based computational engine and object-oriented software architecture replaces the high-cost rack-mount embedded computers of previous systems.

  17. Adaptive network models of collective decision making in swarming systems.

    PubMed

    Chen, Li; Huepe, Cristián; Gross, Thilo

    2016-08-01

    We consider a class of adaptive network models where links can only be created or deleted between nodes in different states. These models provide an approximate description of a set of systems where nodes represent agents moving in physical or abstract space, the state of each node represents the agent's heading direction, and links indicate mutual awareness. We show analytically that the adaptive network description captures a phase transition to collective motion in some swarming systems, such as the Vicsek model, and that the properties of this transition are determined by the number of states (discrete heading directions) that can be accessed by each agent.

  18. Adaptive network models of collective decision making in swarming systems

    NASA Astrophysics Data System (ADS)

    Chen, Li; Huepe, Cristián; Gross, Thilo

    2016-08-01

    We consider a class of adaptive network models where links can only be created or deleted between nodes in different states. These models provide an approximate description of a set of systems where nodes represent agents moving in physical or abstract space, the state of each node represents the agent's heading direction, and links indicate mutual awareness. We show analytically that the adaptive network description captures a phase transition to collective motion in some swarming systems, such as the Vicsek model, and that the properties of this transition are determined by the number of states (discrete heading directions) that can be accessed by each agent.

  19. Emergent “quantum” theory in complex adaptive systems

    NASA Astrophysics Data System (ADS)

    Minic, Djordje; Pajevic, Sinisa

    2016-03-01

    Motivated by the question of stability, in this paper we argue that an effective quantum-like theory can emerge in complex adaptive systems. In the concrete example of stochastic Lotka-Volterra dynamics, the relevant effective “Planck constant” associated with such emergent “quantum” theory has the dimensions of the square of the unit of time. Such an emergent quantum-like theory has inherently nonclassical stability as well as coherent properties that are not, in principle, endangered by thermal fluctuations and therefore might be of crucial importance in complex adaptive systems.

  20. Adaptive network models of collective decision making in swarming systems.

    PubMed

    Chen, Li; Huepe, Cristián; Gross, Thilo

    2016-08-01

    We consider a class of adaptive network models where links can only be created or deleted between nodes in different states. These models provide an approximate description of a set of systems where nodes represent agents moving in physical or abstract space, the state of each node represents the agent's heading direction, and links indicate mutual awareness. We show analytically that the adaptive network description captures a phase transition to collective motion in some swarming systems, such as the Vicsek model, and that the properties of this transition are determined by the number of states (discrete heading directions) that can be accessed by each agent. PMID:27627342

  1. Robust control of a bimorph mirror for adaptive optics systems.

    PubMed

    Baudouin, Lucie; Prieur, Christophe; Guignard, Fabien; Arzelier, Denis

    2008-07-10

    We apply robust control techniques to an adaptive optics system including a dynamic model of the deformable mirror. The dynamic model of the mirror is a modification of the usual plate equation. We propose also a state-space approach to model the turbulent phase. A continuous time control of our model is suggested, taking into account the frequential behavior of the turbulent phase. An H(infinity) controller is designed in an infinite-dimensional setting. Because of the multivariable nature of the control problem involved in adaptive optics systems, a significant improvement is obtained with respect to traditional single input-single output methods.

  2. Adaptive Modeling of the International Space Station Electrical Power System

    NASA Technical Reports Server (NTRS)

    Thomas, Justin Ray

    2007-01-01

    Software simulations provide NASA engineers the ability to experiment with spacecraft systems in a computer-imitated environment. Engineers currently develop software models that encapsulate spacecraft system behavior. These models can be inaccurate due to invalid assumptions, erroneous operation, or system evolution. Increasing accuracy requires manual calibration and domain-specific knowledge. This thesis presents a method for automatically learning system models without any assumptions regarding system behavior. Data stream mining techniques are applied to learn models for critical portions of the International Space Station (ISS) Electrical Power System (EPS). We also explore a knowledge fusion approach that uses traditional engineered EPS models to supplement the learned models. We observed that these engineered EPS models provide useful background knowledge to reduce predictive error spikes when confronted with making predictions in situations that are quite different from the training scenarios used when learning the model. Evaluations using ISS sensor data and existing EPS models demonstrate the success of the adaptive approach. Our experimental results show that adaptive modeling provides reductions in model error anywhere from 80% to 96% over these existing models. Final discussions include impending use of adaptive modeling technology for ISS mission operations and the need for adaptive modeling in future NASA lunar and Martian exploration.

  3. Adaptive Q-S (lag, anticipated, and complete) time-varying synchronization and parameters identification of uncertain delayed neural networks

    NASA Astrophysics Data System (ADS)

    Yu, Wenwu; Cao, Jinde

    2006-06-01

    In this paper, a new type of generalized Q-S (lag, anticipated, and complete) time-varying synchronization is defined. Adaptive Q-S (lag, anticipated, and complete) time-varying synchronization and parameters identification of uncertain delayed neural networks have been considered, where the delays are multiple time-varying delays. A novel control method is given by using the Lyapunov functional method. With this new and effective method, parameters identification and Q-S (lag, anticipated, and complete) time-varying synchronization can be achieved simultaneously. Simulation results are given to justify the theoretical analysis in this paper.

  4. Substructure System Identification for Finite Element Model Updating

    NASA Technical Reports Server (NTRS)

    Craig, Roy R., Jr.; Blades, Eric L.

    1997-01-01

    This report summarizes research conducted under a NASA grant on the topic 'Substructure System Identification for Finite Element Model Updating.' The research concerns ongoing development of the Substructure System Identification Algorithm (SSID Algorithm), a system identification algorithm that can be used to obtain mathematical models of substructures, like Space Shuttle payloads. In the present study, particular attention was given to the following topics: making the algorithm robust to noisy test data, extending the algorithm to accept experimental FRF data that covers a broad frequency bandwidth, and developing a test analytical model (TAM) for use in relating test data to reduced-order finite element models.

  5. Automated frequency domain system identification of a large space structure

    NASA Technical Reports Server (NTRS)

    Yam, Y.; Bayard, D. S.; Hadaegh, F. Y.; Mettler, E.; Milman, M. H.

    1989-01-01

    This paper presents the development and experimental results of an automated on-orbit system identification method for large flexible spacecraft that yields estimated quantities to support on-line design and tuning of robust high performance control systems. The procedure consists of applying an input to the plant, obtaining an output, and then conducting nonparametric identification to yield the spectral estimate of the system transfer function. A parametric model is determined by curve fitting the spectral estimate to a rational transfer function. The identification method has been demonstrated experimentally on the Large Spacecraft Control Laboratory in JPL.

  6. Functional identification of biological neural networks using reservoir adaptation for point processes.

    PubMed

    Gürel, Tayfun; Rotter, Stefan; Egert, Ulrich

    2010-08-01

    The complexity of biological neural networks does not allow to directly relate their biophysical properties to the dynamics of their electrical activity. We present a reservoir computing approach for functionally identifying a biological neural network, i.e. for building an artificial system that is functionally equivalent to the reference biological network. Employing feed-forward and recurrent networks with fading memory, i.e. reservoirs, we propose a point process based learning algorithm to train the internal parameters of the reservoir and the connectivity between the reservoir and the memoryless readout neurons. Specifically, the model is an Echo State Network (ESN) with leaky integrator neurons, whose individual leakage time constants are also adapted. The proposed ESN algorithm learns a predictive model of stimulus-response relations in in vitro and simulated networks, i.e. it models their response dynamics. Receiver Operating Characteristic (ROC) curve analysis indicates that these ESNs can imitate the response signal of a reference biological network. Reservoir adaptation improved the performance of an ESN over readout-only training methods in many cases. This also held for adaptive feed-forward reservoirs, which had no recurrent dynamics. We demonstrate the predictive power of these ESNs on various tasks with cultured and simulated biological neural networks.

  7. Decision-making in healthcare as a complex adaptive system.

    PubMed

    Kuziemsky, Craig

    2016-01-01

    Healthcare transformation requires a change in how the business of healthcare is done. Traditional decision-making approaches based on stable and predictable systems are inappropriate in healthcare because of the complex nature of healthcare delivery. This article reviews challenges to using traditional decision-making approaches in healthcare and how insight from Complex Adaptive Systems (CAS) could support healthcare management. The article also provides a system model to guide decision-making in healthcare as a CAS.

  8. Recombinant cold-adapted trypsin I from Atlantic cod-expression, purification, and identification.

    PubMed

    Jónsdóttir, Gudrún; Bjarnason, Jón Bragi; Gudmundsdóttir, Agústa

    2004-01-01

    Atlantic cod trypsin I is a cold-adapted proteolytic enzyme exhibiting approximately 20 times higher catalytic efficiency (kcat/KM) than its mesophilic bovine counterpart for the simple amide substrate BAPNA. In general, cold-adapted proteolytic enzymes are sensitive to autolytic degradation, thermal inactivation as well as molecular aggregation, even at temperatures as low as 18-25 degrees C which may explain the problems observed with their expression, activation, and purification. Prior to the data presented here, there have been no reports in the literature on the expression of psychrophilic or cold-adapted proteolytic enzymes from fish. Nevertheless, numerous cold-adapted proteolytic microbial enzymes have been successfully expressed in bacteria and yeast. This report describes successful expression, activation, and purification of the recombinant cod trypsin I in the His-Patch ThioFusion Escherichia coli expression system. The E. coli pThioHis expression vector used in the study enabled the formation of a fusion protein between a highly soluble fraction of HP-thioredoxin contained in the vector and the N-terminal end of the precursor form of cod trypsin I. The HP-thioredoxin part of the fusion protein binds to a metal-chelating ProBond column, which facilitated its purification. The cod trypsin I part of the purified fusion protein was released by proteolytic cleavage, resulting in concomitant activation of the recombinant enzyme. The recombinant cod trypsin I was purified to homogeneity on a trypsin-specific benzamidine affinity column. The identity of the recombinant enzyme was demonstrated by electrophoresis and chromatography.

  9. Quantitative adaptation analytics for assessing dynamic systems of systems: LDRD Final Report

    SciTech Connect

    Gauthier, John H.; Miner, Nadine E.; Wilson, Michael L.; Le, Hai D.; Kao, Gio K.; Melander, Darryl J.; Longsine, Dennis Earl; Vander Meer, Jr., Robert C.

    2015-01-01

    Our society is increasingly reliant on systems and interoperating collections of systems, known as systems of systems (SoS). These SoS are often subject to changing missions (e.g., nation- building, arms-control treaties), threats (e.g., asymmetric warfare, terrorism), natural environments (e.g., climate, weather, natural disasters) and budgets. How well can SoS adapt to these types of dynamic conditions? This report details the results of a three year Laboratory Directed Research and Development (LDRD) project aimed at developing metrics and methodologies for quantifying the adaptability of systems and SoS. Work products include: derivation of a set of adaptability metrics, a method for combining the metrics into a system of systems adaptability index (SoSAI) used to compare adaptability of SoS designs, development of a prototype dynamic SoS (proto-dSoS) simulation environment which provides the ability to investigate the validity of the adaptability metric set, and two test cases that evaluate the usefulness of a subset of the adaptability metrics and SoSAI for distinguishing good from poor adaptability in a SoS. Intellectual property results include three patents pending: A Method For Quantifying Relative System Adaptability, Method for Evaluating System Performance, and A Method for Determining Systems Re-Tasking.

  10. An adaptive robust controller for time delay maglev transportation systems

    NASA Astrophysics Data System (ADS)

    Milani, Reza Hamidi; Zarabadipour, Hassan; Shahnazi, Reza

    2012-12-01

    For engineering systems, uncertainties and time delays are two important issues that must be considered in control design. Uncertainties are often encountered in various dynamical systems due to modeling errors, measurement noises, linearization and approximations. Time delays have always been among the most difficult problems encountered in process control. In practical applications of feedback control, time delay arises frequently and can severely degrade closed-loop system performance and in some cases, drives the system to instability. Therefore, stability analysis and controller synthesis for uncertain nonlinear time-delay systems are important both in theory and in practice and many analytical techniques have been developed using delay-dependent Lyapunov function. In the past decade the magnetic and levitation (maglev) transportation system as a new system with high functionality has been the focus of numerous studies. However, maglev transportation systems are highly nonlinear and thus designing controller for those are challenging. The main topic of this paper is to design an adaptive robust controller for maglev transportation systems with time-delay, parametric uncertainties and external disturbances. In this paper, an adaptive robust control (ARC) is designed for this purpose. It should be noted that the adaptive gain is derived from Lyapunov-Krasovskii synthesis method, therefore asymptotic stability is guaranteed.

  11. Self-characterization of linear and nonlinear adaptive optics systems.

    PubMed

    Hampton, Peter J; Conan, Rodolphe; Keskin, Onur; Bradley, Colin; Agathoklis, Pan

    2008-01-10

    We present methods used to determine the linear or nonlinear static response and the linear dynamic response of an adaptive optics (AO) system. This AO system consists of a nonlinear microelectromechanical systems deformable mirror (DM), a linear tip-tilt mirror (TTM), a control computer, and a Shack-Hartmann wavefront sensor. The system is modeled using a single-input-single-output structure to determine the one-dimensional transfer function of the dynamic response of the chain of system hardware. An AO system has been shown to be able to characterize its own response without additional instrumentation. Experimentally determined models are given for a TTM and a DM. PMID:18188192

  12. Adaptive comanagement for building resilience in social-ecological systems.

    PubMed

    Olsson, Per; Folke, Carl; Berkes, Fikret

    2004-07-01

    Ecosystems are complex adaptive systems that require flexible governance with the ability to respond to environmental feedback. We present, through examples from Sweden and Canada, the development of adaptive comanagement systems, showing how local groups self-organize, learn, and actively adapt to and shape change with social networks that connect institutions and organizations across levels and scales and that facilitate information flows. The development took place through a sequence of responses to environmental events that widened the scope of local management from a particular issue or resource to a broad set of issues related to ecosystem processes across scales and from individual actors, to group of actors to multiple-actor processes. The results suggest that the institutional and organizational landscapes should be approached as carefully as the ecological in order to clarify features that contribute to the resilience of social-ecological systems. These include the following: vision, leadership, and trust; enabling legislation that creates social space for ecosystem management; funds for responding to environmental change and for remedial action; capacity for monitoring and responding to environmental feedback; information flow through social networks; the combination of various sources of information and knowledge; and sense-making and arenas of collaborative learning for ecosystem management. We propose that the self-organizing process of adaptive comanagement development, facilitated by rules and incentives of higher levels, has the potential to expand desirable stability domains of a region and make social-ecological systems more robust to change. PMID:15383875

  13. Complex Adaptive Systems as Metaphors for Organizational Management

    ERIC Educational Resources Information Center

    Palmberg, Klara

    2009-01-01

    Purpose: The purpose of this paper is to explore the concept of complex adaptive systems (CAS) from the perspective of managing organizations, to describe and explore the management principles in a case study of an organization with unconventional ways of management and to present a tentative model for managing organizations as CAS--system…

  14. Modeling Students' Memory for Application in Adaptive Educational Systems

    ERIC Educational Resources Information Center

    Pelánek, Radek

    2015-01-01

    Human memory has been thoroughly studied and modeled in psychology, but mainly in laboratory setting under simplified conditions. For application in practical adaptive educational systems we need simple and robust models which can cope with aspects like varied prior knowledge or multiple-choice questions. We discuss and evaluate several models of…

  15. Classrooms as Complex Adaptive Systems: A Relational Model

    ERIC Educational Resources Information Center

    Burns, Anne; Knox, John S.

    2011-01-01

    In this article, we describe and model the language classroom as a complex adaptive system (see Logan & Schumann, 2005). We argue that linear, categorical descriptions of classroom processes and interactions do not sufficiently explain the complex nature of classrooms, and cannot account for how classroom change occurs (or does not occur), over…

  16. The New Trends in Adaptive Educational Hypermedia Systems

    ERIC Educational Resources Information Center

    Somyürek, Sibel

    2015-01-01

    This paper aims to give a general review of existing literature on adaptive educational hypermedia systems and to reveal technological trends and approaches within these studies. Fifty-six studies conducted between 2002 and 2012 were examined, to identify prominent themes and approaches. According to the content analysis, the new technological…

  17. Adaptive mechanism-based congestion control for networked systems

    NASA Astrophysics Data System (ADS)

    Liu, Zhi; Zhang, Yun; Chen, C. L. Philip

    2013-03-01

    In order to assure the communication quality in network systems with heavy traffic and limited bandwidth, a new ATRED (adaptive thresholds random early detection) congestion control algorithm is proposed for the congestion avoidance and resource management of network systems. Different to the traditional AQM (active queue management) algorithms, the control parameters of ATRED are not configured statically, but dynamically adjusted by the adaptive mechanism. By integrating with the adaptive strategy, ATRED alleviates the tuning difficulty of RED (random early detection) and shows a better control on the queue management, and achieve a more robust performance than RED under varying network conditions. Furthermore, a dynamic transmission control protocol-AQM control system using ATRED controller is introduced for the systematic analysis. It is proved that the stability of the network system can be guaranteed when the adaptive mechanism is finely designed. Simulation studies show the proposed ATRED algorithm achieves a good performance in varying network environments, which is superior to the RED and Gentle-RED algorithm, and providing more reliable service under varying network conditions.

  18. Modeling of Biometric Identification System Using the Colored Petri Nets

    NASA Astrophysics Data System (ADS)

    Petrosyan, G. R.; Ter-Vardanyan, L. A.; Gaboutchian, A. V.

    2015-05-01

    In this paper we present a model of biometric identification system transformed into Petri Nets. Petri Nets, as a graphical and mathematical tool, provide a uniform environment for modelling, formal analysis, and design of discrete event systems. The main objective of this paper is to introduce the fundamental concepts of Petri Nets to the researchers and practitioners, both from identification systems, who are involved in the work in the areas of modelling and analysis of biometric identification types of systems, as well as those who may potentially be involved in these areas. In addition, the paper introduces high-level Petri Nets, as Colored Petri Nets (CPN). In this paper the model of Colored Petri Net describes the identification process much simpler.

  19. 47 CFR 25.281 - Automatic Transmitter Identification System (ATIS).

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... (ATIS). 25.281 Section 25.281 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES SATELLITE COMMUNICATIONS Technical Operations § 25.281 Automatic Transmitter Identification System (ATIS). All satellite uplink transmissions carrying broadband video information shall...

  20. 47 CFR 25.281 - Automatic Transmitter Identification System (ATIS).

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... (ATIS). 25.281 Section 25.281 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES SATELLITE COMMUNICATIONS Technical Operations § 25.281 Automatic Transmitter Identification System (ATIS). All satellite uplink transmissions carrying broadband video information shall...

  1. 47 CFR 25.281 - Automatic Transmitter Identification System (ATIS).

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... (ATIS). 25.281 Section 25.281 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES SATELLITE COMMUNICATIONS Technical Operations § 25.281 Automatic Transmitter Identification System (ATIS). All satellite uplink transmissions carrying broadband video information shall...

  2. 47 CFR 25.281 - Automatic Transmitter Identification System (ATIS).

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... (ATIS). 25.281 Section 25.281 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES SATELLITE COMMUNICATIONS Technical Operations § 25.281 Automatic Transmitter Identification System (ATIS). All satellite uplink transmissions carrying broadband video information shall...

  3. Development of an Automatic Identification System Autonomous Positioning System.

    PubMed

    Hu, Qing; Jiang, Yi; Zhang, Jingbo; Sun, Xiaowen; Zhang, Shufang

    2015-11-11

    In order to overcome the vulnerability of the global navigation satellite system (GNSS) and provide robust position, navigation and time (PNT) information in marine navigation, the autonomous positioning system based on ranging-mode Automatic Identification System (AIS) is presented in the paper. The principle of the AIS autonomous positioning system (AAPS) is investigated, including the position algorithm, the signal measurement technique, the geometric dilution of precision, the time synchronization technique and the additional secondary factor correction technique. In order to validate the proposed AAPS, a verification system has been established in the Xinghai sea region of Dalian (China). Static and dynamic positioning experiments are performed. The original function of the AIS in the AAPS is not influenced. The experimental results show that the positioning precision of the AAPS is better than 10 m in the area with good geometric dilution of precision (GDOP) by the additional secondary factor correction technology. This is the most economical solution for a land-based positioning system to complement the GNSS for the navigation safety of vessels sailing along coasts.

  4. Development of an Automatic Identification System Autonomous Positioning System.

    PubMed

    Hu, Qing; Jiang, Yi; Zhang, Jingbo; Sun, Xiaowen; Zhang, Shufang

    2015-01-01

    In order to overcome the vulnerability of the global navigation satellite system (GNSS) and provide robust position, navigation and time (PNT) information in marine navigation, the autonomous positioning system based on ranging-mode Automatic Identification System (AIS) is presented in the paper. The principle of the AIS autonomous positioning system (AAPS) is investigated, including the position algorithm, the signal measurement technique, the geometric dilution of precision, the time synchronization technique and the additional secondary factor correction technique. In order to validate the proposed AAPS, a verification system has been established in the Xinghai sea region of Dalian (China). Static and dynamic positioning experiments are performed. The original function of the AIS in the AAPS is not influenced. The experimental results show that the positioning precision of the AAPS is better than 10 m in the area with good geometric dilution of precision (GDOP) by the additional secondary factor correction technology. This is the most economical solution for a land-based positioning system to complement the GNSS for the navigation safety of vessels sailing along coasts. PMID:26569258

  5. Development of an Automatic Identification System Autonomous Positioning System

    PubMed Central

    Hu, Qing; Jiang, Yi; Zhang, Jingbo; Sun, Xiaowen; Zhang, Shufang

    2015-01-01

    In order to overcome the vulnerability of the global navigation satellite system (GNSS) and provide robust position, navigation and time (PNT) information in marine navigation, the autonomous positioning system based on ranging-mode Automatic Identification System (AIS) is presented in the paper. The principle of the AIS autonomous positioning system (AAPS) is investigated, including the position algorithm, the signal measurement technique, the geometric dilution of precision, the time synchronization technique and the additional secondary factor correction technique. In order to validate the proposed AAPS, a verification system has been established in the Xinghai sea region of Dalian (China). Static and dynamic positioning experiments are performed. The original function of the AIS in the AAPS is not influenced. The experimental results show that the positioning precision of the AAPS is better than 10 m in the area with good geometric dilution of precision (GDOP) by the additional secondary factor correction technology. This is the most economical solution for a land-based positioning system to complement the GNSS for the navigation safety of vessels sailing along coasts. PMID:26569258

  6. Guiding climate change adaptation within vulnerable natural resource management systems.

    PubMed

    Bardsley, Douglas K; Sweeney, Susan M

    2010-05-01

    Climate change has the potential to compromise the sustainability of natural resources in Mediterranean climatic systems, such that short-term reactive responses will increasingly be insufficient to ensure effective management. There is a simultaneous need for both the clear articulation of the vulnerabilities of specific management systems to climate risk, and the development of appropriate short- and long-term strategic planning responses that anticipate environmental change or allow for sustainable adaptive management in response to trends in resource condition. Governments are developing climate change adaptation policy frameworks, but without the recognition of the importance of responding strategically, regional stakeholders will struggle to manage future climate risk. In a partnership between the South Australian Government, the Adelaide and Mt Lofty Ranges Natural Resource Management Board and the regional community, a range of available research approaches to support regional climate change adaptation decision-making, were applied and critically examined, including: scenario modelling; applied and participatory Geographical Information Systems modelling; environmental risk analysis; and participatory action learning. As managers apply ideas for adaptation within their own biophysical and socio-cultural contexts, there would be both successes and failures, but a learning orientation to societal change will enable improvements over time. A base-line target for regional responses to climate change is the ownership of the issue by stakeholders, which leads to an acceptance that effective actions to adapt are now both possible and vitally important. Beyond such baseline knowledge, the research suggests that there is a range of tools from the social and physical sciences available to guide adaptation decision-making.

  7. Guiding Climate Change Adaptation Within Vulnerable Natural Resource Management Systems

    NASA Astrophysics Data System (ADS)

    Bardsley, Douglas K.; Sweeney, Susan M.

    2010-05-01

    Climate change has the potential to compromise the sustainability of natural resources in Mediterranean climatic systems, such that short-term reactive responses will increasingly be insufficient to ensure effective management. There is a simultaneous need for both the clear articulation of the vulnerabilities of specific management systems to climate risk, and the development of appropriate short- and long-term strategic planning responses that anticipate environmental change or allow for sustainable adaptive management in response to trends in resource condition. Governments are developing climate change adaptation policy frameworks, but without the recognition of the importance of responding strategically, regional stakeholders will struggle to manage future climate risk. In a partnership between the South Australian Government, the Adelaide and Mt Lofty Ranges Natural Resource Management Board and the regional community, a range of available research approaches to support regional climate change adaptation decision-making, were applied and critically examined, including: scenario modelling; applied and participatory Geographical Information Systems modelling; environmental risk analysis; and participatory action learning. As managers apply ideas for adaptation within their own biophysical and socio-cultural contexts, there would be both successes and failures, but a learning orientation to societal change will enable improvements over time. A base-line target for regional responses to climate change is the ownership of the issue by stakeholders, which leads to an acceptance that effective actions to adapt are now both possible and vitally important. Beyond such baseline knowledge, the research suggests that there is a range of tools from the social and physical sciences available to guide adaptation decision-making.

  8. Integrated modeling of the GMT laser tomography adaptive optics system

    NASA Astrophysics Data System (ADS)

    Piatrou, Piotr

    2014-08-01

    Laser Tomography Adaptive Optics (LTAO) is one of adaptive optics systems planned for the Giant Magellan Telescope (GMT). End-to-end simulation tools that are able to cope with the complexity and computational burden of the AO systems to be installed on the extremely large telescopes such as GMT prove to be an integral part of the GMT LTAO system development endeavors. SL95, the Fortran 95 Simulation Library, is one of the software tools successfully used for the LTAO system end-to-end simulations. The goal of SL95 project is to provide a complete set of generic, richly parameterized mathematical models for key elements of the segmented telescope wavefront control systems including both active and adaptive optics as well as the models for atmospheric turbulence, extended light sources like Laser Guide Stars (LGS), light propagation engines and closed-loop controllers. The library is implemented as a hierarchical collection of classes capable of mutual interaction, which allows one to assemble complex wavefront control system configurations with multiple interacting control channels. In this paper we demonstrate the SL95 capabilities by building an integrated end-to-end model of the GMT LTAO system with 7 control channels: LGS tomography with Adaptive Secondary and on-instrument deformable mirrors, tip-tilt and vibration control, LGS stabilization, LGS focus control, truth sensor-based dynamic noncommon path aberration rejection, pupil position control, SLODAR-like embedded turbulence profiler. The rich parameterization of the SL95 classes allows to build detailed error budgets propagating through the system multiple errors and perturbations such as turbulence-, telescope-, telescope misalignment-, segment phasing error-, non-common path-induced aberrations, sensor noises, deformable mirror-to-sensor mis-registration, vibration, temporal errors, etc. We will present a short description of the SL95 architecture, as well as the sample GMT LTAO system simulation

  9. Research of Uncertainty Reasoning in Pineapple Disease Identification System

    NASA Astrophysics Data System (ADS)

    Liu, Liqun; Fan, Haifeng

    In order to deal with the uncertainty of evidences mostly existing in pineapple disease identification system, a reasoning model based on evidence credibility factor was established. The uncertainty reasoning method is discussed,including: uncertain representation of knowledge, uncertain representation of rules, uncertain representation of multi-evidences and update of reasoning rules. The reasoning can fully reflect the uncertainty in disease identification and reduce the influence of subjective factors on the accuracy of the system.

  10. Flexible Ubiquitous Learning Management System Adapted to Learning Context

    NASA Astrophysics Data System (ADS)

    Jeong, Ji-Seong; Kim, Mihye; Park, Chan; Yoo, Jae-Soo; Yoo, Kwan-Hee

    This paper proposes a u-learning management system (ULMS) appropriate to the ubiquitous learning environment, with emphasis on the significance of context awareness and adaptation in learning. The proposed system supports the basic functions of an e-learning management system and incorporates a number of tools and additional features to provide a more customized learning service. The proposed system automatically corresponds to various forms of user terminal without modifying the existing system. The functions, formats, and course learning activities of the system are dynamically and adaptively constructed at runtime according to user terminals, course types, pedagogical goals as well as student characteristics and learning context. A prototype for university use has been implemented to demonstrate and evaluate the proposed approach. We regard the proposed ULMS as an ideal u-learning system because it can not only lead students into continuous and mobile 'anytime, anywhere' learning using any kind of terminal, but can also foster enhanced self-directed learning through the establishment of an adaptive learning environment.

  11. Adaptive backstepping slide mode control of pneumatic position servo system

    NASA Astrophysics Data System (ADS)

    Ren, Haipeng; Fan, Juntao

    2016-06-01

    With the price decreasing of the pneumatic proportional valve and the high performance micro controller, the simple structure and high tracking performance pneumatic servo system demonstrates more application potential in many fields. However, most existing control methods with high tracking performance need to know the model information and to use pressure sensor. This limits the application of the pneumatic servo system. An adaptive backstepping slide mode control method is proposed for pneumatic position servo system. The proposed method designs adaptive slide mode controller using backstepping design technique. The controller parameter adaptive law is derived from Lyapunov analysis to guarantee the stability of the system. A theorem is testified to show that the state of closed-loop system is uniformly bounded, and the closed-loop system is stable. The advantages of the proposed method include that system dynamic model parameters are not required for the controller design, uncertain parameters bounds are not need, and the bulk and expensive pressure sensor is not needed as well. Experimental results show that the designed controller can achieve better tracking performance, as compared with some existing methods.

  12. Adaptive control system having hedge unit and related apparatus and methods

    NASA Technical Reports Server (NTRS)

    Johnson, Eric Norman (Inventor); Calise, Anthony J. (Inventor)

    2007-01-01

    The invention includes an adaptive control system used to control a plant. The adaptive control system includes a hedge unit that receives at least one control signal and a plant state signal. The hedge unit generates a hedge signal based on the control signal, the plant state signal, and a hedge model including a first model having one or more characteristics to which the adaptive control system is not to adapt, and a second model not having the characteristic(s) to which the adaptive control system is not to adapt. The hedge signal is used in the adaptive control system to remove the effect of the characteristic from a signal supplied to an adaptation law unit of the adaptive control system so that the adaptive control system does not adapt to the characteristic in controlling the plant.

  13. Adaptive control system having hedge unit and related apparatus and methods

    NASA Technical Reports Server (NTRS)

    Johnson, Eric Norman (Inventor); Calise, Anthony J. (Inventor)

    2003-01-01

    The invention includes an adaptive control system used to control a plant. The adaptive control system includes a hedge unit that receives at least one control signal and a plant state signal. The hedge unit generates a hedge signal based on the control signal, the plant state signal, and a hedge model including a first model having one or more characteristics to which the adaptive control system is not to adapt, and a second model not having the characteristic(s) to which the adaptive control system is not to adapt. The hedge signal is used in the adaptive control system to remove the effect of the characteristic from a signal supplied to an adaptation law unit of the adaptive control system so that the adaptive control system does not adapt to the characteristic in controlling the plant.

  14. Adaptive conventional power system stabilizer based on artificial neural network

    SciTech Connect

    Kothari, M.L.; Segal, R.; Ghodki, B.K.

    1995-12-31

    This paper deals with an artificial neural network (ANN) based adaptive conventional power system stabilizer (PSS). The ANN comprises an input layer, a hidden layer and an output layer. The input vector to the ANN comprises real power (P) and reactive power (Q), while the output vector comprises optimum PSS parameters. A systematic approach for generating training set covering wide range of operating conditions, is presented. The ANN has been trained using back-propagation training algorithm. Investigations reveal that the dynamic performance of ANN based adaptive conventional PSS is quite insensitive to wide variations in loading conditions.

  15. Adaptive hybrid optimal quantum control for imprecisely characterized systems.

    PubMed

    Egger, D J; Wilhelm, F K

    2014-06-20

    Optimal quantum control theory carries a huge promise for quantum technology. Its experimental application, however, is often hindered by imprecise knowledge of the input variables, the quantum system's parameters. We show how to overcome this by adaptive hybrid optimal control, using a protocol named Ad-HOC. This protocol combines open- and closed-loop optimal control by first performing a gradient search towards a near-optimal control pulse and then an experimental fidelity estimation with a gradient-free method. For typical settings in solid-state quantum information processing, adaptive hybrid optimal control enhances gate fidelities by an order of magnitude, making optimal control theory applicable and useful. PMID:24996074

  16. Time-frequency analysis for parametric and non-parametric identification of nonlinear dynamical systems

    NASA Astrophysics Data System (ADS)

    Frank Pai, P.

    2013-04-01

    This paper points out the differences between linear and nonlinear system identification tasks, shows that time-frequency analysis is most appropriate for nonlinearity identification, and presents advanced signal processing techniques that combine time-frequency decomposition and perturbation methods for parametric and non-parametric identification of nonlinear dynamical systems. Hilbert-Huang transform (HHT) is a recent data-driven adaptive time-frequency analysis technique that combines the use of empirical mode decomposition (EMD) and Hilbert transform (HT). Because EMD does not use predetermined basis functions and function orthogonality for component extraction, HHT provides more concise component decomposition and more accurate time-frequency analysis than the short-time Fourier transform and wavelet transform for extraction of system characteristics and nonlinearities. However, HHT's accuracy seriously suffers from the end effect caused by the discontinuity-induced Gibbs' phenomenon. Moreover, because HHT requires a long set of data obtained by high-frequency sampling, it is not appropriate for online frequency tracking. This paper presents a conjugate-pair decomposition (CPD) method that requires only a few recent data points sampled at a low-frequency for sliding-window point-by-point adaptive time-frequency analysis and can be used for online frequency tracking. To improve adaptive time-frequency analysis, a methodology is developed by combining EMD and CPD for noise filtering in the time domain, reducing the end effect, and dissolving other mathematical and numerical problems in time-frequency analysis. For parametric identification of a nonlinear system, the methodology processes one steady-state response and/or one free damped transient response and uses amplitude-dependent dynamic characteristics derived from perturbation analysis to determine the type and order of nonlinearity and system parameters. For non-parametric identification, the methodology

  17. A Self-Adaptive Missile Guidance System for Statistical Inputs

    NASA Technical Reports Server (NTRS)

    Peery, H. Rodney

    1960-01-01

    A method of designing a self-adaptive missile guidance system is presented. The system inputs are assumed to be known in a statistical sense only. Newton's modified Wiener theory is utilized in the design of the system and to establish the performance criterion. The missile is assumed to be a beam rider, to have a g limiter, and to operate over a flight envelope where the open-loop gain varies by a factor of 20. It is shown that the percent of time that missile acceleration limiting occurs can be used effectively to adjust the coefficients of the Wiener filter. The result is a guidance system which adapts itself to a changing environment and gives essentially optimum filtering and minimum miss distance.

  18. Variable Neural Adaptive Robust Control: A Switched System Approach

    SciTech Connect

    Lian, Jianming; Hu, Jianghai; Zak, Stanislaw H.

    2015-05-01

    Variable neural adaptive robust control strategies are proposed for the output tracking control of a class of multi-input multi-output uncertain systems. The controllers incorporate a variable-structure radial basis function (RBF) network as the self-organizing approximator for unknown system dynamics. The variable-structure RBF network solves the problem of structure determination associated with fixed-structure RBF networks. It can determine the network structure on-line dynamically by adding or removing radial basis functions according to the tracking performance. The structure variation is taken into account in the stability analysis of the closed-loop system using a switched system approach with the aid of the piecewise quadratic Lyapunov function. The performance of the proposed variable neural adaptive robust controllers is illustrated with simulations.

  19. Parameter identification for nonlinear aerodynamic systems

    NASA Technical Reports Server (NTRS)

    Pearson, Allan E.

    1992-01-01

    Continuing work on frequency analysis for transfer function identification is discussed. A new study was initiated into a 'weighted' least squares algorithm within the context of the Fourier modulating function approach. The first phase of applying these techniques to the F-18 flight data is nearing completion, and these results are summarized.

  20. System integration of pattern recognition, adaptive aided, upper limb prostheses

    NASA Technical Reports Server (NTRS)

    Lyman, J.; Freedy, A.; Solomonow, M.

    1975-01-01

    The requirements for successful integration of a computer aided control system for multi degree of freedom artificial arms are discussed. Specifications are established for a system which shares control between a human amputee and an automatic control subsystem. The approach integrates the following subsystems: (1) myoelectric pattern recognition, (2) adaptive computer aiding; (3) local reflex control; (4) prosthetic sensory feedback; and (5) externally energized arm with the functions of prehension, wrist rotation, elbow extension and flexion and humeral rotation.

  1. An information adaptive system study report and development plan

    NASA Technical Reports Server (NTRS)

    Ataras, W. S.; Eng, K.; Morone, J. J.; Beaudet, P. R.; Chin, R.

    1980-01-01

    The purpose of the information adaptive system (IAS) study was to determine how some selected Earth resource applications may be processed onboard a spacecraft and to provide a detailed preliminary IAS design for these applications. Detailed investigations of a number of applications were conducted with regard to IAS and three were selected for further analysis. Areas of future research and development include algorithmic specifications, system design specifications, and IAS recommended time lines.

  2. Autonomous Navigation System Using a Fuzzy Adaptive Nonlinear H∞ Filter

    PubMed Central

    Outamazirt, Fariz; Li, Fu; Yan, Lin; Nemra, Abdelkrim

    2014-01-01

    Although nonlinear H∞ (NH∞) filters offer good performance without requiring assumptions concerning the characteristics of process and/or measurement noises, they still require additional tuning parameters that remain fixed and that need to be determined through trial and error. To address issues associated with NH∞ filters, a new SINS/GPS sensor fusion scheme known as the Fuzzy Adaptive Nonlinear H∞ (FANH∞) filter is proposed for the Unmanned Aerial Vehicle (UAV) localization problem. Based on a real-time Fuzzy Inference System (FIS), the FANH∞ filter continually adjusts the higher order of the Taylor development thorough adaptive bounds (δi) and adaptive disturbance attenuation (γ), which significantly increases the UAV localization performance. The results obtained using the FANH∞ navigation filter are compared to the NH∞ navigation filter results and are validated using a 3D UAV flight scenario. The comparison proves the efficiency and robustness of the UAV localization process using the FANH∞ filter. PMID:25244587

  3. Autonomous navigation system using a fuzzy adaptive nonlinear H∞ filter.

    PubMed

    Outamazirt, Fariz; Li, Fu; Yan, Lin; Nemra, Abdelkrim

    2014-09-19

    Although nonlinear H∞ (NH∞) filters offer good performance without requiring assumptions concerning the characteristics of process and/or measurement noises, they still require additional tuning parameters that remain fixed and that need to be determined through trial and error. To address issues associated with NH∞ filters, a new SINS/GPS sensor fusion scheme known as the Fuzzy Adaptive Nonlinear H∞ (FANH∞) filter is proposed for the Unmanned Aerial Vehicle (UAV) localization problem. Based on a real-time Fuzzy Inference System (FIS), the FANH∞ filter continually adjusts the higher order of the Taylor development thorough adaptive bounds  and adaptive disturbance attenuation , which significantly increases the UAV localization performance. The results obtained using the FANH∞ navigation filter are compared to the NH∞ navigation filter results and are validated using a 3D UAV flight scenario. The comparison proves the efficiency and robustness of the UAV localization process using the FANH∞ filter.

  4. Autonomous navigation system using a fuzzy adaptive nonlinear H∞ filter.

    PubMed

    Outamazirt, Fariz; Li, Fu; Yan, Lin; Nemra, Abdelkrim

    2014-01-01

    Although nonlinear H∞ (NH∞) filters offer good performance without requiring assumptions concerning the characteristics of process and/or measurement noises, they still require additional tuning parameters that remain fixed and that need to be determined through trial and error. To address issues associated with NH∞ filters, a new SINS/GPS sensor fusion scheme known as the Fuzzy Adaptive Nonlinear H∞ (FANH∞) filter is proposed for the Unmanned Aerial Vehicle (UAV) localization problem. Based on a real-time Fuzzy Inference System (FIS), the FANH∞ filter continually adjusts the higher order of the Taylor development thorough adaptive bounds  and adaptive disturbance attenuation , which significantly increases the UAV localization performance. The results obtained using the FANH∞ navigation filter are compared to the NH∞ navigation filter results and are validated using a 3D UAV flight scenario. The comparison proves the efficiency and robustness of the UAV localization process using the FANH∞ filter. PMID:25244587

  5. Selective adaptation to "oddball" sounds by the human auditory system.

    PubMed

    Simpson, Andrew J R; Harper, Nicol S; Reiss, Joshua D; McAlpine, David

    2014-01-29

    Adaptation to both common and rare sounds has been independently reported in neurophysiological studies using probabilistic stimulus paradigms in small mammals. However, the apparent sensitivity of the mammalian auditory system to the statistics of incoming sound has not yet been generalized to task-related human auditory perception. Here, we show that human listeners selectively adapt to novel sounds within scenes unfolding over minutes. Listeners' performance in an auditory discrimination task remains steady for the most common elements within the scene but, after the first minute, performance improves for distinct and rare (oddball) sound elements, at the expense of rare sounds that are relatively less distinct. Our data provide the first evidence of enhanced coding of oddball sounds in a human auditory discrimination task and suggest the existence of an adaptive mechanism that tracks the long-term statistics of sounds and deploys coding resources accordingly. PMID:24478375

  6. Modeling neural adaptation in the frog auditory system

    NASA Astrophysics Data System (ADS)

    Wotton, Janine; McArthur, Kimberly; Bohara, Amit; Ferragamo, Michael; Megela Simmons, Andrea

    2005-09-01

    Extracellular recordings from the auditory midbrain, Torus semicircularis, of the leopard frog reveal a wide diversity of tuning patterns. Some cells seem to be well suited for time-based coding of signal envelope, and others for rate-based coding of signal frequency. Adaptation for ongoing stimuli plays a significant role in shaping the frequency-dependent response rate at different levels of the frog auditory system. Anuran auditory-nerve fibers are unusual in that they reveal frequency-dependent adaptation [A. L. Megela, J. Acoust. Soc. Am. 75, 1155-1162 (1984)], and therefore provide rate-based input. In order to examine the influence of these peripheral inputs on central responses, three layers of auditory neurons were modeled to examine short-term neural adaptation to pure tones and complex signals. The response of each neuron was simulated with a leaky integrate and fire model, and adaptation was implemented by means of an increasing threshold. Auditory-nerve fibers, dorsal medullary nucleus neurons, and toral cells were simulated and connected in three ascending layers. Modifying the adaptation properties of the peripheral fibers dramatically alters the response at the midbrain. [Work supported by NOHR to M.J.F.; Gustavus Presidential Scholarship to K.McA.; NIH DC05257 to A.M.S.

  7. Development of adaptive helicopter seat systems for aircrew vibration mitigation

    NASA Astrophysics Data System (ADS)

    Chen, Yong; Wickramasinghe, Viresh; Zimcik, David G.

    2008-03-01

    Helicopter aircrews are exposed to high levels of whole body vibration during flight. This paper presents the results of an investigation of adaptive seat mount approaches to reduce helicopter aircrew whole body vibration levels. A flight test was conducted on a four-blade helicopter and showed that the currently used passive seat systems were not able to provide satisfactory protection to the helicopter aircrew in both front-back and vertical directions. Long-term exposure to the measured whole body vibration environment may cause occupational health issues such as spine and neck strain injuries for aircrew. In order to address this issue, a novel adaptive seat mount concept was developed to mitigate the vibration levels transmitted to the aircrew body. For proof-of-concept demonstration, a miniature modal shaker was properly aligned between the cabin floor and the seat frame to provide adaptive actuation authority. Adaptive control laws were developed to reduce the vibration transmitted to the aircrew body, especially the helmet location in order to minimize neck and spine injuries. Closed-loop control test have been conducted on a full-scale helicopter seat with a mannequin configuration and a large mechanical shaker was used to provide representative helicopter vibration profiles to the seat frame. Significant vibration reductions to the vertical and front-back vibration modes have been achieved simultaneously, which verified the technical readiness of the adaptive mount approach for full-scale flight test on the vehicle.

  8. Neuro adaptive control for aerospace and distributed systems

    NASA Astrophysics Data System (ADS)

    Das, Abhijit

    Nonlinear and adaptive control is generally considered one of the most effective techniques for stabilizing complex nonlinear systems, where linear control techniques may fail completely. Thousands of research papers are published on either theory or applications of nonlinear and adaptive control. But often one obvious question arises how to implement these techniques in real life model? The best answer that one can think of is to develop simple nonlinear control laws which are easy to implement. Moreover for controlling multi-agent systems, it is often required to distribute the control laws based on limited information available among the agents. This research provides some of these issues in the following way. a) Autopilot design for Aerospace systems: this research developes adaptive backstepping and dynamic inversion methods with internal dynamics stabilization for the quadrotor. Quadrotor helicopter models usually show two main characteristics. First, strong coupling among the system states and second, under-actuation where many states are to be controlled with few control inputs. Due to these unique characteristics, the design of stabilizing control inputs is always challenging for quadrotor models. To confront these problems, first, a dynamic inversion technique with zero dynamics stabilization loop is introduced to a practical quadrotor model, second, an adaptive-backstepping technique is developed to a lagrangian quadrotor model. The stabilizing control laws for both of these techniques are developed using on Lyapunov based method; and b) Coordination of multi-agent systems: coordination among multiple agents is generally done based on balanced or bi-directed communication graph models. If the agents are nonlinear and passive then for a balanced graph model synchronization is possible. But, for other than balanced and bi-directed graph models, it is difficult to synchronize nonlinear systems. Moreover, the performance of synchronization is normally

  9. Homeostatic Regulation of Memory Systems and Adaptive Decisions

    PubMed Central

    Mizumori, Sheri JY; Jo, Yong Sang

    2013-01-01

    While it is clear that many brain areas process mnemonic information, understanding how their interactions result in continuously adaptive behaviors has been a challenge. A homeostatic-regulated prediction model of memory is presented that considers the existence of a single memory system that is based on a multilevel coordinated and integrated network (from cells to neural systems) that determines the extent to which events and outcomes occur as predicted. The “multiple memory systems of the brain” have in common output that signals errors in the prediction of events and/or their outcomes, although these signals differ in terms of what the error signal represents (e.g., hippocampus: context prediction errors vs. midbrain/striatum: reward prediction errors). The prefrontal cortex likely plays a pivotal role in the coordination of prediction analysis within and across prediction brain areas. By virtue of its widespread control and influence, and intrinsic working memory mechanisms. Thus, the prefrontal cortex supports the flexible processing needed to generate adaptive behaviors and predict future outcomes. It is proposed that prefrontal cortex continually and automatically produces adaptive responses according to homeostatic regulatory principles: prefrontal cortex may serve as a controller that is intrinsically driven to maintain in prediction areas an experience-dependent firing rate set point that ensures adaptive temporally and spatially resolved neural responses to future prediction errors. This same drive by prefrontal cortex may also restore set point firing rates after deviations (i.e. prediction errors) are detected. In this way, prefrontal cortex contributes to reducing uncertainty in prediction systems. An emergent outcome of this homeostatic view may be the flexible and adaptive control that prefrontal cortex is known to implement (i.e. working memory) in the most challenging of situations. Compromise to any of the prediction circuits should result

  10. A Comparison of a Brain-Based Adaptive System and a Manual Adaptable System for Invoking Automation

    NASA Technical Reports Server (NTRS)

    Bailey, Nathan R.; Scerbo, Mark W.; Freeman, Frederick G.; Mikulka, Peter J.; Scott, Lorissa A.

    2004-01-01

    Two experiments are presented that examine alternative methods for invoking automation. In each experiment, participants were asked to perform simultaneously a monitoring task and a resource management task as well as a tracking task that changed between automatic and manual modes. The monitoring task required participants to detect failures of an automated system to correct aberrant conditions under either high or low system reliability. Performance on each task was assessed as well as situation awareness and subjective workload. In the first experiment, half of the participants worked with a brain-based system that used their EEG signals to switch the tracking task between automatic and manual modes. The remaining participants were yoked to participants from the adaptive condition and received the same schedule of mode switches, but their EEG had no effect on the automation. Within each group, half of the participants were assigned to either the low or high reliability monitoring task. In addition, within each combination of automation invocation and system reliability, participants were separated into high and low complacency potential groups. The results revealed no significant effects of automation invocation on the performance measures; however, the high complacency individuals demonstrated better situation awareness when working with the adaptive automation system. The second experiment was the same as the first with one important exception. Automation was invoked manually. Thus, half of the participants pressed a button to invoke automation for 10 s. The remaining participants were yoked to participants from the adaptable condition and received the same schedule of mode switches, but they had no control over the automation. The results showed that participants who could invoke automation performed more poorly on the resource management task and reported higher levels of subjective workload. Further, those who invoked automation more frequently performed

  11. Contingency support using adaptive telemetry extractor and expert system technologies

    NASA Astrophysics Data System (ADS)

    Bryant, Thomas; Cruse, Bryant; Wende, Charles

    The 'telemetry analysis logic for operations support' prototype system constitutes an expert system that is charged with contingency planning for the NASA Hubble Space Telescope (HST); this system has demonstrated the feasibility of using an adaptive telemetry extractor/reformatter that is integrated with an expert system. A test case generated by a simulator has demonstrated the reduction of the time required for analysis of a complex series of failures to a few minutes, from the hour usually required. The HST's telemetry extractor will be able to read real-time engineering telemetry streams and disk-based data. Telemetry format changes will be handled almost instantaneously.

  12. Embedded intelligent adaptive PI controller for an electromechanical system.

    PubMed

    El-Nagar, Ahmad M

    2016-09-01

    In this study, an intelligent adaptive controller approach using the interval type-2 fuzzy neural network (IT2FNN) is presented. The proposed controller consists of a lower level proportional - integral (PI) controller, which is the main controller and an upper level IT2FNN which tuning on-line the parameters of a PI controller. The proposed adaptive PI controller based on IT2FNN (API-IT2FNN) is implemented practically using the Arduino DUE kit for controlling the speed of a nonlinear DC motor-generator system. The parameters of the IT2FNN are tuned on-line using back-propagation algorithm. The Lyapunov theorem is used to derive the stability and convergence of the IT2FNN. The obtained experimental results, which are compared with other controllers, demonstrate that the proposed API-IT2FNN is able to improve the system response over a wide range of system uncertainties. PMID:27342993

  13. Robust adaptive dynamic programming and feedback stabilization of nonlinear systems.

    PubMed

    Jiang, Yu; Jiang, Zhong-Ping

    2014-05-01

    This paper studies the robust optimal control design for a class of uncertain nonlinear systems from a perspective of robust adaptive dynamic programming (RADP). The objective is to fill up a gap in the past literature of adaptive dynamic programming (ADP) where dynamic uncertainties or unmodeled dynamics are not addressed. A key strategy is to integrate tools from modern nonlinear control theory, such as the robust redesign and the backstepping techniques as well as the nonlinear small-gain theorem, with the theory of ADP. The proposed RADP methodology can be viewed as an extension of ADP to uncertain nonlinear systems. Practical learning algorithms are developed in this paper, and have been applied to the controller design problems for a jet engine and a one-machine power system. PMID:24808035

  14. A portable air jet actuator device for mechanical system identification.

    PubMed

    Belden, Jesse; Staats, Wayne L; Mazumdar, Anirban; Hunter, Ian W

    2011-03-01

    System identification of limb mechanics can help diagnose ailments and can aid in the optimization of robotic limb control parameters and designs. An interesting fluid phenomenon--the Coandă effect--is utilized in a portable actuator to provide a stochastic binary force disturbance to a limb system. The design of the actuator is approached with the goal of creating a portable device which could be deployed on human or robotic limbs for in situ mechanical system identification. The viability of the device is demonstrated by identifying the parameters of an underdamped elastic beam system with fixed inertia and stiffness and variable damping. The nonparametric compliance impulse response yielded from the system identification is modeled as a second-order system and the resultant parameters are found to be in excellent agreement with those found using more traditional system identification techniques. The current design could be further miniaturized and developed as a portable, wireless, unrestrained mechanical system identification instrument for less intrusive and more widespread use. PMID:21456788

  15. A portable air jet actuator device for mechanical system identification

    NASA Astrophysics Data System (ADS)

    Belden, Jesse; Staats, Wayne L.; Mazumdar, Anirban; Hunter, Ian W.

    2011-03-01

    System identification of limb mechanics can help diagnose ailments and can aid in the optimization of robotic limb control parameters and designs. An interesting fluid phenomenon—the Coandă effect—is utilized in a portable actuator to provide a stochastic binary force disturbance to a limb system. The design of the actuator is approached with the goal of creating a portable device which could be deployed on human or robotic limbs for in situ mechanical system identification. The viability of the device is demonstrated by identifying the parameters of an underdamped elastic beam system with fixed inertia and stiffness and variable damping. The nonparametric compliance impulse response yielded from the system identification is modeled as a second-order system and the resultant parameters are found to be in excellent agreement with those found using more traditional system identification techniques. The current design could be further miniaturized and developed as a portable, wireless, unrestrained mechanical system identification instrument for less intrusive and more widespread use.

  16. System identification methods for aircraft flight control development and validation

    NASA Technical Reports Server (NTRS)

    Tischler, Mark B.

    1995-01-01

    System-identification methods compose a mathematical model, or series of models, from measurements of inputs and outputs of dynamic systems. The extracted models allow the characterization of the response of the overall aircraft or component subsystem behavior, such as actuators and on-board signal processing algorithms. This paper discusses the use of frequency-domain system-identification methods for the development and integration of aircraft flight-control systems. The extraction and analysis of models of varying complexity from nonparametric frequency-responses to transfer-functions and high-order state-space representations is illustrated using the Comprehensive Identification from FrEquency Responses (CIFER) system-identification facility. Results are presented for test data of numerous flight and simulation programs at the Ames Research Center including rotorcraft, fixed-wing aircraft, advanced short takeoff and vertical landing (ASTOVL), vertical/short takeoff and landing (V/STOL), tiltrotor aircraft, and rotor experiments in the wind tunnel. Excellent system characterization and dynamic response prediction is achieved for this wide class of systems. Examples illustrate the role of system-identification technology in providing an integrated flow of dynamic response data around the entire life-cycle of aircraft development from initial specifications, through simulation and bench testing, and into flight-test optimization.

  17. Teaching Optics and Systems Engineering With Adaptive Optics Workbenches

    NASA Astrophysics Data System (ADS)

    Harrington, D. M.; Ammons, M.; Hunter, L.; Max, C.; Hoffmann, M.; Pitts, M.; Armstrong, J. D.

    2010-12-01

    Adaptive optics workbenches are fully functional optical systems that can be used to illustrate and teach a variety of concepts and cognitive processes. Four systems have been funded, designed and constructed by various institutions and people as part of education programs associated with the Center for Adaptive Optics, the Professional Development Program and the Institute for Scientist & Engineer Educators. Activities can range from first-year undergraduate explorations to professional level training. These workbenches have been used in many venues including the Center for Adaptive Optics AO Summer School, the Maui Community College-hosted Akamai Maui Short Course, classrooms, training of new staff in laboratories and other venues. The activity content has focused on various elements of systems thinking, characterization, feedback and system control, basic optics and optical alignment as well as advanced topics such as phase conjugation, wave-front sensing and correction concepts, and system design. The workbenches have slightly different designs and performance capabilities. We describe here outlines for several activities utilizing these different designs and some examples of common student learner outcomes and experiences.

  18. Fault Analysis of Space Station DC Power Systems-Using Neural Network Adaptive Wavelets to Detect Faults

    NASA Technical Reports Server (NTRS)

    Momoh, James A.; Wang, Yanchun; Dolce, James L.

    1997-01-01

    This paper describes the application of neural network adaptive wavelets for fault diagnosis of space station power system. The method combines wavelet transform with neural network by incorporating daughter wavelets into weights. Therefore, the wavelet transform and neural network training procedure become one stage, which avoids the complex computation of wavelet parameters and makes the procedure more straightforward. The simulation results show that the proposed method is very efficient for the identification of fault locations.

  19. Application of network control systems for adaptive optics

    NASA Astrophysics Data System (ADS)

    Eager, Robert J.

    2008-04-01

    The communication architecture for most pointing, tracking, and high order adaptive optics control systems has been based on a centralized point-to-point and bus based approach. With the increased use of larger arrays and multiple sensors, actuators and processing nodes, these evolving systems require decentralized control, modularity, flexibility redundancy, integrated diagnostics, dynamic resource allocation, and ease of maintenance to support a wide range of experiments. Network control systems provide all of these critical functionalities. This paper begins with a quick overview of adaptive optics as a control system and communication architecture. It then provides an introduction to network control systems, identifying the key design areas that impact system performance. The paper then discusses the performance test results of a fielded network control system used to implement an adaptive optics system comprised of: a 10KHz, 32x32 spatial selfreferencing interferometer wave front sensor, a 705 channel "Tweeter" deformable mirror, a 177 channel "Woofer" deformable mirror, ten processing nodes, and six data acquisition nodes. The reconstructor algorithm utilized a modulo-2pi wave front phase measurement and a least-squares phase un-wrapper with branch point correction. The servo control algorithm is a hybrid of exponential and infinite impulse response controllers, with tweeter-to-woofer saturation offloading. This system achieved a first-pixel-out to last-mirror-voltage latency of 86 microseconds, with the network accounting for 4 microseconds of the measured latency. Finally, the extensibility of this architecture will be illustrated, by detailing the integration of a tracking sub-system into the existing network.

  20. Adaptive fuzzy sliding mode control scheme for uncertain systems

    NASA Astrophysics Data System (ADS)

    Noroozi, Navid; Roopaei, Mehdi; Jahromi, M. Zolghadri

    2009-11-01

    Most physical systems inherently contain nonlinearities which are commonly unknown to the system designer. Therefore, in modeling and analysis of such dynamic systems, one needs to handle unknown nonlinearities and/or uncertain parameters. This paper proposes a new adaptive tracking fuzzy sliding mode controller for a class of nonlinear systems in the presence of uncertainties and external disturbances. The main contribution of the proposed method is that the structure of the controlled system is partially unknown and does not require the bounds of uncertainty and disturbance of the system to be known; meanwhile, the chattering phenomenon that frequently appears in the conventional variable structure systems is also eliminated without deteriorating the system robustness. The performance of the proposed approach is evaluated for two well-known benchmark problems. The simulation results illustrate the effectiveness of our proposed controller.

  1. A modular and hybrid connectionist system for speaker identification.

    PubMed

    Bennani, Y

    1995-07-01

    This paper presents and evaluates a modular/hybrid connectionist system for speaker identification. Modularity has emerged as a powerful technique for reducing the complexity of connectionist systems, and allowing a priori knowledge to be incorporated into their design. Text-independent speaker identification is an inherently complex task where the amount of training data is often limited. It thus provides an ideal domain to test the validity of the modular/hybrid connectionist approach. To achieve such identification, we develop, in this paper, an architecture based upon the cooperation of several connectionist modules, and a Hidden Markov Model module. When tested on a population of 102 speakers extracted from the DARPA-TIMIT database, perfect identification was obtained.

  2. Risk-return relationship in a complex adaptive system.

    PubMed

    Song, Kunyu; An, Kenan; Yang, Guang; Huang, Jiping

    2012-01-01

    For survival and development, autonomous agents in complex adaptive systems involving the human society must compete against or collaborate with others for sharing limited resources or wealth, by using different methods. One method is to invest, in order to obtain payoffs with risk. It is a common belief that investments with a positive risk-return relationship (namely, high risk high return and vice versa) are dominant over those with a negative risk-return relationship (i.e., high risk low return and vice versa) in the human society; the belief has a notable impact on daily investing activities of investors. Here we investigate the risk-return relationship in a model complex adaptive system, in order to study the effect of both market efficiency and closeness that exist in the human society and play an important role in helping to establish traditional finance/economics theories. We conduct a series of computer-aided human experiments, and also perform agent-based simulations and theoretical analysis to confirm the experimental observations and reveal the underlying mechanism. We report that investments with a negative risk-return relationship have dominance over those with a positive risk-return relationship instead in such a complex adaptive systems. We formulate the dynamical process for the system's evolution, which helps to discover the different role of identical and heterogeneous preferences. This work might be valuable not only to complexity science, but also to finance and economics, to management and social science, and to physics. PMID:22479416

  3. Digital adaptive optics line-scanning confocal imaging system.

    PubMed

    Liu, Changgeng; Kim, Myung K

    2015-01-01

    A digital adaptive optics line-scanning confocal imaging (DAOLCI) system is proposed by applying digital holographic adaptive optics to a digital form of line-scanning confocal imaging system. In DAOLCI, each line scan is recorded by a digital hologram, which allows access to the complex optical field from one slice of the sample through digital holography. This complex optical field contains both the information of one slice of the sample and the optical aberration of the system, thus allowing us to compensate for the effect of the optical aberration, which can be sensed by a complex guide star hologram. After numerical aberration compensation, the corrected optical fields of a sequence of line scans are stitched into the final corrected confocal image. In DAOLCI, a numerical slit is applied to realize the confocality at the sensor end. The width of this slit can be adjusted to control the image contrast and speckle noise for scattering samples. DAOLCI dispenses with the hardware pieces, such as Shack–Hartmann wavefront sensor and deformable mirror, and the closed-loop feedbacks adopted in the conventional adaptive optics confocal imaging system, thus reducing the optomechanical complexity and cost. Numerical simulations and proof-of-principle experiments are presented that demonstrate the feasibility of this idea.

  4. Risk-return relationship in a complex adaptive system.

    PubMed

    Song, Kunyu; An, Kenan; Yang, Guang; Huang, Jiping

    2012-01-01

    For survival and development, autonomous agents in complex adaptive systems involving the human society must compete against or collaborate with others for sharing limited resources or wealth, by using different methods. One method is to invest, in order to obtain payoffs with risk. It is a common belief that investments with a positive risk-return relationship (namely, high risk high return and vice versa) are dominant over those with a negative risk-return relationship (i.e., high risk low return and vice versa) in the human society; the belief has a notable impact on daily investing activities of investors. Here we investigate the risk-return relationship in a model complex adaptive system, in order to study the effect of both market efficiency and closeness that exist in the human society and play an important role in helping to establish traditional finance/economics theories. We conduct a series of computer-aided human experiments, and also perform agent-based simulations and theoretical analysis to confirm the experimental observations and reveal the underlying mechanism. We report that investments with a negative risk-return relationship have dominance over those with a positive risk-return relationship instead in such a complex adaptive systems. We formulate the dynamical process for the system's evolution, which helps to discover the different role of identical and heterogeneous preferences. This work might be valuable not only to complexity science, but also to finance and economics, to management and social science, and to physics.

  5. Digital adaptive optics line-scanning confocal imaging system

    PubMed Central

    Liu, Changgeng; Kim, Myung K.

    2015-01-01

    Abstract. A digital adaptive optics line-scanning confocal imaging (DAOLCI) system is proposed by applying digital holographic adaptive optics to a digital form of line-scanning confocal imaging system. In DAOLCI, each line scan is recorded by a digital hologram, which allows access to the complex optical field from one slice of the sample through digital holography. This complex optical field contains both the information of one slice of the sample and the optical aberration of the system, thus allowing us to compensate for the effect of the optical aberration, which can be sensed by a complex guide star hologram. After numerical aberration compensation, the corrected optical fields of a sequence of line scans are stitched into the final corrected confocal image. In DAOLCI, a numerical slit is applied to realize the confocality at the sensor end. The width of this slit can be adjusted to control the image contrast and speckle noise for scattering samples. DAOLCI dispenses with the hardware pieces, such as Shack–Hartmann wavefront sensor and deformable mirror, and the closed-loop feedbacks adopted in the conventional adaptive optics confocal imaging system, thus reducing the optomechanical complexity and cost. Numerical simulations and proof-of-principle experiments are presented that demonstrate the feasibility of this idea. PMID:26140334

  6. Optical axis jitter rejection for double overlapped adaptive optics systems

    NASA Astrophysics Data System (ADS)

    Luo, Qi; Luo, Xi; Li, Xinyang

    2016-04-01

    Optical axis jitters, or vibrations, which arise from wind shaking and structural oscillations of optical platforms, etc., cause a deleterious impact on the performance of adaptive optics systems. When conventional integrators are utilized to reject such high frequency and narrow-band disturbance, the benefits are quite small despite their acceptable capabilities to reject atmospheric turbulence. In our case, two suits of complete adaptive optics systems called double overlapped adaptive optics systems (DOAOS) are used to counteract both optical jitters and atmospheric turbulence. A novel algorithm aiming to remove vibrations is proposed by resorting to combine the Smith predictor and notch filer. With the help of loop shaping method, the algorithm will lead to an effective and stable controller, which makes the characteristics of error transfer function close to notch filters. On the basis of the spectral analysis of observed data, the peak frequency and bandwidth of vibrations can be identified in advance. Afterwards, the number of notch filters and their parameters will be determined using coordination descending method. The relationship between controller parameters and filtering features is discussed, and the robustness of the controller against varying parameters of the control object is investigated. Preliminary experiments are carried out to validate the proposed algorithms. The overall control performance of DOAOS is simulated. Results show that time delays are a limit of the performance, but the algorithm can be successfully implemented on our systems, which indicate that it has a great potential to reject jitters.

  7. Digital adaptive optics line-scanning confocal imaging system.

    PubMed

    Liu, Changgeng; Kim, Myung K

    2015-01-01

    A digital adaptive optics line-scanning confocal imaging (DAOLCI) system is proposed by applying digital holographic adaptive optics to a digital form of line-scanning confocal imaging system. In DAOLCI, each line scan is recorded by a digital hologram, which allows access to the complex optical field from one slice of the sample through digital holography. This complex optical field contains both the information of one slice of the sample and the optical aberration of the system, thus allowing us to compensate for the effect of the optical aberration, which can be sensed by a complex guide star hologram. After numerical aberration compensation, the corrected optical fields of a sequence of line scans are stitched into the final corrected confocal image. In DAOLCI, a numerical slit is applied to realize the confocality at the sensor end. The width of this slit can be adjusted to control the image contrast and speckle noise for scattering samples. DAOLCI dispenses with the hardware pieces, such as Shack–Hartmann wavefront sensor and deformable mirror, and the closed-loop feedbacks adopted in the conventional adaptive optics confocal imaging system, thus reducing the optomechanical complexity and cost. Numerical simulations and proof-of-principle experiments are presented that demonstrate the feasibility of this idea. PMID:26140334

  8. Digital adaptive optics line-scanning confocal imaging system

    NASA Astrophysics Data System (ADS)

    Liu, Changgeng; Kim, Myung K.

    2015-11-01

    A digital adaptive optics line-scanning confocal imaging (DAOLCI) system is proposed by applying digital holographic adaptive optics to a digital form of line-scanning confocal imaging system. In DAOLCI, each line scan is recorded by a digital hologram, which allows access to the complex optical field from one slice of the sample through digital holography. This complex optical field contains both the information of one slice of the sample and the optical aberration of the system, thus allowing us to compensate for the effect of the optical aberration, which can be sensed by a complex guide star hologram. After numerical aberration compensation, the corrected optical fields of a sequence of line scans are stitched into the final corrected confocal image. In DAOLCI, a numerical slit is applied to realize the confocality at the sensor end. The width of this slit can be adjusted to control the image contrast and speckle noise for scattering samples. DAOLCI dispenses with the hardware pieces, such as Shack-Hartmann wavefront sensor and deformable mirror, and the closed-loop feedbacks adopted in the conventional adaptive optics confocal imaging system, thus reducing the optomechanical complexity and cost. Numerical simulations and proof-of-principle experiments are presented that demonstrate the feasibility of this idea.

  9. Identification of cardiovascular dilution systems by contrast ultrasound.

    PubMed

    Mischi, Massimo; Jansen, Annemieke H M; Korsten, Hendrikus H M

    2007-03-01

    Indicator dilution techniques permit accurate measurements of important cardiovascular parameters, such as pulmonary blood volume (PBV) and ejection fraction (EF). However, their use is limited by the need for central catheterization. Contrast ultrasonography allows overcoming this problem. PBV and EF can be measured by a dilution system identification algorithm after detection of multiple dilution curves by an ultrasound scanner. In this paper, we present a system identification method that exploits the a priori knowledge on the dilution system and finds the optimum parameters for the parametric model representing the dilution system impulse response. No subsequent model interpolation is needed. Volume measurements show accurate in-vitro results and clinical feasibility, while 50 EF measurements in patients show a 0.88 correlation coefficient with echocardiographic biplane estimates. In conclusion, adding a priori knowledge to the system identification algorithm leads to increased accuracy and robustness of the method for PBV and EF measurements.

  10. Application of an adaptive blade control algorithm to a gust alleviation system

    NASA Technical Reports Server (NTRS)

    Saito, S.

    1984-01-01

    The feasibility of an adaptive control system designed to alleviate helicopter gust induced vibration was analytically investigated for an articulated rotor system. This control system is based on discrete optimal control theory, and is composed of a set of measurements (oscillatory hub forces and moments), an identification system using a Kalman filter, a control system based on the minimization of the quadratic performance function, and a simulation system of the helicopter rotor. The gust models are step and sinusoidal vertical gusts. Control inputs are selected at the gust frequency, subharmonic frequency, and superharmonic frequency, and are superimposed on the basic collective and cyclic control inputs. The response to be reduced is selected to be that at the gust frequency because this is the dominant response compared with sub- and superharmonics. Numerical calculations show that the adaptive blade pitch control algorithm satisfactorily alleviates the hub gust response. Almost 100 percent reduction of the perturbation thrust response to a step gust and more than 50 percent reduction to a sinusoidal gust are achieved in the numerical simulations.

  11. Application of an adaptive blade control algorithm to a gust alleviation system

    NASA Technical Reports Server (NTRS)

    Saito, S.

    1983-01-01

    The feasibility of an adaptive control system designed to alleviate helicopter gust induced vibration was analytically investigated for an articulated rotor system. This control system is based on discrete optimal control theory, and is composed of a set of measurements (oscillatory hub forces and moments), an identification system using a Kalman filter, a control system based on the minimization of the quadratic performance function, and a simulation system of the helicopter rotor. The gust models are step and sinusoidal vertical gusts. Control inputs are selected at the gust frequency, subharmonic frequency, and superharmonic frequency, and are superimposed on the basic collective and cyclic control inputs. The response to be reduced is selected to be that at the gust frequency because this is the dominant response compared with sub- and superharmonics. Numerical calculations show that the adaptive blade pitch control algorithm satisfactorily alleviates the hub gust response. Almost 100% reduction of the perturbation thrust response to a step gust and more than 50% reduction to a sinusoidal gust are achieved in the numerical simulations.

  12. Evaluation of the Biolog automated microbial identification system

    NASA Technical Reports Server (NTRS)

    Klingler, J. M.; Stowe, R. P.; Obenhuber, D. C.; Groves, T. O.; Mishra, S. K.; Pierson, D. L.

    1992-01-01

    Biolog's identification system was used to identify 39 American Type Culture Collection reference taxa and 45 gram-negative isolates from water samples. Of the reference strains, 98% were identified to genus level and 76% to species level within 4 to 24 h. Identification of some authentic strains of Enterobacter, Klebsiella, and Serratia was unreliable. A total of 93% of the water isolates were identified.

  13. Model of adaptive temporal development of structured finite systems

    NASA Astrophysics Data System (ADS)

    Patera, Jiri; Shaw, Gordon L.; Slansky, Richard; Leng, Xiaodan

    1989-07-01

    The weight systems of level-zero representations of affine Kac-Moody algebras provide an appropriate kinematical framework for studying structured finite systems with adaptive temporal development. Much of the structure is determined by Lie algebra theory, so it is possible to restrict greatly the connection space and analytic results are possible. The time development of these systems often evolves to cyclic temporal-spatial patterns, depending on the definition of the dynamics. The purpose of this paper is to set up the mathematical formalism for this ``memory in Lie algebras'' class of models. An illustration is used to show the kinds of complex behavior that occur in simple cases.

  14. Performance predictions for the Keck telescope adaptive optics system

    SciTech Connect

    Gavel, D.T.; Olivier, S.S.

    1995-08-07

    The second Keck ten meter telescope (Keck-11) is slated to have an infrared-optimized adaptive optics system in the 1997--1998 time frame. This system will provide diffraction-limited images in the 1--3 micron region and the ability to use a diffraction-limited spectroscopy slit. The AO system is currently in the preliminary design phase and considerable analysis has been performed in order to predict its performance under various seeing conditions. In particular we have investigated the point-spread function, energy through a spectroscopy slit, crowded field contrast, object limiting magnitude, field of view, and sky coverage with natural and laser guide stars.

  15. Robust adaptive dynamic programming with an application to power systems.

    PubMed

    Jiang, Yu; Jiang, Zhong-Ping

    2013-07-01

    This brief presents a novel framework of robust adaptive dynamic programming (robust-ADP) aimed at computing globally stabilizing and suboptimal control policies in the presence of dynamic uncertainties. A key strategy is to integrate ADP theory with techniques in modern nonlinear control with a unique objective of filling up a gap in the past literature of ADP without taking into account dynamic uncertainties. Neither the system dynamics nor the system order are required to be precisely known. As an illustrative example, the computational algorithm is applied to the controller design of a two-machine power system. PMID:24808528

  16. CRISPR-Cas systems: Prokaryotes upgrade to adaptive immunity.

    PubMed

    Barrangou, Rodolphe; Marraffini, Luciano A

    2014-04-24

    Clustered regularly interspaced short palindromic repeats (CRISPR), and associated proteins (Cas) comprise the CRISPR-Cas system, which confers adaptive immunity against exogenic elements in many bacteria and most archaea. CRISPR-mediated immunization occurs through the uptake of DNA from invasive genetic elements such as plasmids and viruses, followed by its integration into CRISPR loci. These loci are subsequently transcribed and processed into small interfering RNAs that guide nucleases for specific cleavage of complementary sequences. Conceptually, CRISPR-Cas shares functional features with the mammalian adaptive immune system, while also exhibiting characteristics of Lamarckian evolution. Because immune markers spliced from exogenous agents are integrated iteratively in CRISPR loci, they constitute a genetic record of vaccination events and reflect environmental conditions and changes over time. Cas endonucleases, which can be reprogrammed by small guide RNAs have shown unprecedented potential and flexibility for genome editing and can be repurposed for numerous DNA targeting applications including transcriptional control.

  17. Low Temperature Shape Memory Alloys for Adaptive, Autonomous Systems Project

    NASA Technical Reports Server (NTRS)

    Falker, John; Zeitlin, Nancy; Williams, Martha; Benafan, Othmane; Fesmire, James

    2015-01-01

    The objective of this joint activity between Kennedy Space Center (KSC) and Glenn Research Center (GRC) is to develop and evaluate the applicability of 2-way SMAs in proof-of-concept, low-temperature adaptive autonomous systems. As part of this low technology readiness (TRL) activity, we will develop and train low-temperature novel, 2-way shape memory alloys (SMAs) with actuation temperatures ranging from 0 C to 150 C. These experimental alloys will also be preliminary tested to evaluate their performance parameters and transformation (actuation) temperatures in low- temperature or cryogenic adaptive proof-of-concept systems. The challenge will be in the development, design, and training of the alloys for 2-way actuation at those temperatures.

  18. CRISPR-Cas systems: prokaryotes upgrade to adaptive immunity

    PubMed Central

    Barrangou, Rodolphe; Marraffini, Luciano A.

    2014-01-01

    Summary Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR), and associated proteins (Cas) comprise the CRISPR-Cas system, which confers adaptive immunity against exogenic elements in many bacteria and most archaea. CRISPR-mediated immunization occurs through the uptake of DNA from invasive genetic elements such as plasmids and viruses, followed by its integration into CRISPR loci. These loci are subsequently transcribed and processed into small interfering RNAs that guide nucleases for specific cleavage of complementary sequences. Conceptually, CRISPR-Cas shares functional features with the mammalian adaptive immune system, while also exhibiting characteristics of Lamarckian evolution. Because immune markers spliced from exogenous agents are integrated iteratively in CRISPR loci, they constitute a genetic record of vaccination events and reflect environmental conditions and changes over time. Cas endonucleases, which can be reprogrammed by small guide RNAs have shown unprecedented potential and flexibility for genome editing, and can be repurposed for numerous DNA targeting applications including transcriptional control. PMID:24766887

  19. A new neuro-FDS definition for indirect adaptive control of unknown nonlinear systems using a method of parameter hopping.

    PubMed

    Boutalis, Yiannis; Theodoridis, Dimitris C; Christodoulou, Manolis A

    2009-04-01

    The indirect adaptive regulation of unknown nonlinear dynamical systems is considered in this paper. The method is based on a new neuro-fuzzy dynamical system (neuro-FDS) definition, which uses the concept of adaptive fuzzy systems (AFSs) operating in conjunction with high-order neural network functions (FHONNFs). Since the plant is considered unknown, we first propose its approximation by a special form of an FDS and then the fuzzy rules are approximated by appropriate HONNFs. Thus, the identification scheme leads up to a recurrent high-order neural network (RHONN), which however takes into account the fuzzy output partitions of the initial FDS. The proposed scheme does not require a priori experts' information on the number and type of input variable membership functions making it less vulnerable to initial design assumptions. Once the system is identified around an operation point, it is regulated to zero adaptively. Weight updating laws for the involved HONNFs are provided, which guarantee that both the identification error and the system states reach zero exponentially fast, while keeping all signals in the closed loop bounded. The existence of the control signal is always assured by introducing a novel method of parameter hopping, which is incorporated in the weight updating law. Simulations illustrate the potency of the method and comparisons with conventional approaches on benchmarking systems are given. Also, the applicability of the method is tested on a direct current (dc) motor system where it is shown that by following the proposed procedure one can obtain asymptotic regulation.

  20. The plasma membrane transport systems and adaptation to salinity.

    PubMed

    Mansour, Mohamed Magdy F

    2014-11-15

    Salt stress represents one of the environmental challenges that drastically affect plant growth and yield. Evidence suggests that glycophytes and halophytes have a salt tolerance mechanisms working at the cellular level, and the plasma membrane (PM) is believed to be one facet of the cellular mechanisms. The responses of the PM transport proteins to salinity in contrasting species/cultivars were discussed. The review provides a comprehensive overview of the recent advances describing the crucial roles that the PM transport systems have in plant adaptation to salt. Several lines of evidence were presented to demonstrate the correlation between the PM transport proteins and adaptation of plants to high salinity. How alterations in these transport systems of the PM allow plants to cope with the salt stress was also addressed. Although inconsistencies exist in some of the information related to the responses of the PM transport proteins to salinity in different species/cultivars, their key roles in adaptation of plants to high salinity is obvious and evident, and cannot be precluded. Despite the promising results, detailed investigations at the cellular/molecular level are needed in some issues of the PM transport systems in response to salinity to further evaluate their implication in salt tolerance.

  1. The plasma membrane transport systems and adaptation to salinity.

    PubMed

    Mansour, Mohamed Magdy F

    2014-11-15

    Salt stress represents one of the environmental challenges that drastically affect plant growth and yield. Evidence suggests that glycophytes and halophytes have a salt tolerance mechanisms working at the cellular level, and the plasma membrane (PM) is believed to be one facet of the cellular mechanisms. The responses of the PM transport proteins to salinity in contrasting species/cultivars were discussed. The review provides a comprehensive overview of the recent advances describing the crucial roles that the PM transport systems have in plant adaptation to salt. Several lines of evidence were presented to demonstrate the correlation between the PM transport proteins and adaptation of plants to high salinity. How alterations in these transport systems of the PM allow plants to cope with the salt stress was also addressed. Although inconsistencies exist in some of the information related to the responses of the PM transport proteins to salinity in different species/cultivars, their key roles in adaptation of plants to high salinity is obvious and evident, and cannot be precluded. Despite the promising results, detailed investigations at the cellular/molecular level are needed in some issues of the PM transport systems in response to salinity to further evaluate their implication in salt tolerance. PMID:25262536

  2. Model abstraction results using state-space system identifications

    NASA Astrophysics Data System (ADS)

    Popken, Douglas A.

    2000-06-01

    In this paper we report on state-space system identification approaches to dynamic behavioral abstraction of military simulation models. Two stochastic simulation models were identified under a variety of scenarios. The `Attrition Simulation' is a model of two opposing forces with multiple weapon system types. The `Mission Simulation' is a model of a squadron of aircraft performing battlefield air interdiction. Four system identification techniques: Maximum Entropy, Compartmental Models, Canonical State-Space Models, and Hidden Markov Models (HMM), were applied to these simulation models. The system identification techniques were evaluated on how well their resulting abstractions replicated the distributions of the simulation states as well as the decision outputs. Encouraging results were achieved by the HMM technique applied to the Attrition Simulation--and by the Maximum Entropy technique applied to the Mission Simulation.

  3. Smart adaptive optic systems using spatial light modulators.

    PubMed

    Clark, N; Banish, M; Ranganath, H S

    1999-01-01

    Many factors contribute to the aberrations induced in an optical system. Atmospheric turbulence between the object and the imaging system, physical or thermal perturbations in optical elements degrade the system's point spread function, and misaligned optics are the primary sources of aberrations that affect image quality. The design of a nonconventional real-time adaptive optic system using a micro-mirror device for wavefront correction is presented. The unconventional compensated imaging system presented offers advantages in speed, cost, power consumption, and weight. A pulsed-coupled neural network is used to as a preprocessor to enhance the performance of the wavefront sensor for low-light applications. Modeling results that characterize the system performance are presented. PMID:18252558

  4. Application of unsymmetric block Lanczos vectors in system identification

    NASA Astrophysics Data System (ADS)

    Kim, H. M., Jr.; Craig, R. R.

    1992-10-01

    This paper demonstrates a new system identification approach of using Lanczos coordinates in place of modal coordinates. Identified experimental Lanczos vectors can be directly used in many structural dynamics analysis applications. A multi-input, multi-output frequency-domain technique was used to extract system matrices and an unsymmetric block Lanczos algorithm was used to reduce the order of the experimental model. A cantilever beam example showed promising results, indicating that a new system identification approach using Lanczos coordinates is worthy of further study.

  5. Design of adaptive control systems by means of self-adjusting transversal filters

    NASA Technical Reports Server (NTRS)

    Merhav, S. J.

    1986-01-01

    The design of closed-loop adaptive control systems based on nonparametric identification was addressed. Implementation is by self-adjusting Least Mean Square (LMS) transversal filters. The design concept is Model Reference Adaptive Control (MRAC). Major issues are to preserve the linearity of the error equations of each LMS filter, and to prevent estimation bias that is due to process or measurement noise, thus providing necessary conditions for the convergence and stability of the control system. The controlled element is assumed to be asymptotically stable and minimum phase. Because of the nonparametric Finite Impulse Response (FIR) estimates provided by the LMS filters, a-priori information on the plant model is needed only in broad terms. Following a survey of control system configurations and filter design considerations, system implementation is shown here in Single Input Single Output (SISO) format which is readily extendable to multivariable forms. In extensive computer simulation studies the controlled element is represented by a second-order system with widely varying damping, natural frequency, and relative degree.

  6. Adaptive and Rational Anticipations in Risk Management Systems and Economy

    NASA Astrophysics Data System (ADS)

    Dubois, Daniel M.; Holmberg, Stig C.

    2010-11-01

    The global financial crisis of year 2009 is explained as a result of uncoordinated risk management decisions in business firms and economic organisations. The underlying reason for this can be found in the current financial system. As the financial market has lost much of its direct coupling to the concrete economy it provides misleading information to economic decision makers at all levels. Hence, the financial system has moved from a state of moderate and slow cyclical fluctuations into a state of fast and chaotic ones. Those misleading decisions can further be described, but not explained, by help of adaptive and rational expectations from macroeconomic theory. In this context, AE, the Adaptive Expectations are related to weak passive Exo-anticipation, and RE, the Rational expectations can be related to a strong, active and design oriented anticipation. The shortcomings of conventional cures, which builds on a reactive paradigm, have already been demonstrated in economic literature and are here further underlined by help of Ashby's "Law of Requisite Variety", Weaver's distinction between systems of "Disorganized Complexity" and those of "Organized Complexity", and Klir's "Reconstructability Analysis". Anticipatory decision-making is hence here proposed as a replacement to current expectation based and passive risk management. An anticipatory model of the business cycle is presented for supporting that proposition. The model, which is an extension of the Kaldor-Kalecki model, includes both retardation and anticipation. While cybernetics with the feedback process in control system deals with an explicit goal or purpose given to a system, the anticipatory system discussed here deals with a behaviour for which the future state of the system is built by the system itself, without explicit goal. A system with weak anticipation is based on a predictive model of the system, while a system with strong anticipation builds its own future by itself. Numerical simulations on

  7. Minimalist identification system based on venous map for security applications

    NASA Astrophysics Data System (ADS)

    Jacinto G., Edwar; Martínez S., Fredy; Martínez S., Fernando

    2015-07-01

    This paper proposes a technique and an algorithm used to build a device for people identification through the processing of a low resolution camera image. The infrared channel is the only information needed, sensing the blood reaction with the proper wave length, and getting a preliminary snapshot of the vascular map of the back side of the hand. The software uses this information to extract the characteristics of the user in a limited area (region of interest, ROI), unique for each user, which applicable to biometric access control devices. This kind of recognition prototypes functions are expensive, but in this case (minimalist design), the biometric equipment only used a low cost camera and the matrix of IR emitters adaptation to construct an economic and versatile prototype, without neglecting the high level of effectiveness that characterizes this kind of identification method.

  8. Complex Generalized Synchronization and Parameter Identification of Nonidentical Nonlinear Complex Systems.

    PubMed

    Wang, Shibing; Wang, Xingyuan; Han, Bo

    2016-01-01

    In this paper, generalized synchronization (GS) is extended from real space to complex space, resulting in a new synchronization scheme, complex generalized synchronization (CGS). Based on Lyapunov stability theory, an adaptive controller and parameter update laws are designed to realize CGS and parameter identification of two nonidentical chaotic (hyperchaotic) complex systems with respect to a given complex map vector. This scheme is applied to synchronize a memristor-based hyperchaotic complex Lü system and a memristor-based chaotic complex Lorenz system, a chaotic complex Chen system and a memristor-based chaotic complex Lorenz system, as well as a memristor-based hyperchaotic complex Lü system and a chaotic complex Lü system with fully unknown parameters. The corresponding numerical simulations illustrate the feasibility and effectiveness of the proposed scheme. PMID:27014879

  9. Complex Generalized Synchronization and Parameter Identification of Nonidentical Nonlinear Complex Systems

    PubMed Central

    Wang, Shibing; Wang, Xingyuan; Han, Bo

    2016-01-01

    In this paper, generalized synchronization (GS) is extended from real space to complex space, resulting in a new synchronization scheme, complex generalized synchronization (CGS). Based on Lyapunov stability theory, an adaptive controller and parameter update laws are designed to realize CGS and parameter identification of two nonidentical chaotic (hyperchaotic) complex systems with respect to a given complex map vector. This scheme is applied to synchronize a memristor-based hyperchaotic complex Lü system and a memristor-based chaotic complex Lorenz system, a chaotic complex Chen system and a memristor-based chaotic complex Lorenz system, as well as a memristor-based hyperchaotic complex Lü system and a chaotic complex Lü system with fully unknown parameters. The corresponding numerical simulations illustrate the feasibility and effectiveness of the proposed scheme. PMID:27014879

  10. An adaptive neuro-control system of synchronous generator for power system stabilization

    SciTech Connect

    Kobayashi, Takenori; Yokoyama, Akihiko

    1996-09-01

    This paper proposes a nonlinear adaptive generator control system using neural networks, called an adaptive neuro-control system (ANCS). This system generates supplementary control signals to conventional controllers and works adaptively in response to changes in operating conditions and network configuration. Through digital time simulations for a one-machine infinite bus test power system, the control performance of the ANCS and advanced controllers such as a linear optimal regulator and a self-tuning regulator is evaluated from the viewpoint of stability enhancement. As a result, the proposed ANCS using neural networks with nonlinear characteristics improves system damping more effectively and more adaptively than the other two controllers designed for the linearized model of the power system.

  11. Decentralized System Identification Using Stochastic Subspace Identification for Wireless Sensor Networks

    PubMed Central

    Cho, Soojin; Park, Jong-Woong; Sim, Sung-Han

    2015-01-01

    Wireless sensor networks (WSNs) facilitate a new paradigm to structural identification and monitoring for civil infrastructure. Conventional structural monitoring systems based on wired sensors and centralized data acquisition systems are costly for installation as well as maintenance. WSNs have emerged as a technology that can overcome such difficulties, making deployment of a dense array of sensors on large civil structures both feasible and economical. However, as opposed to wired sensor networks in which centralized data acquisition and processing is common practice, WSNs require decentralized computing algorithms to reduce data transmission due to the limitation associated with wireless communication. In this paper, the stochastic subspace identification (SSI) technique is selected for system identification, and SSI-based decentralized system identification (SDSI) is proposed to be implemented in a WSN composed of Imote2 wireless sensors that measure acceleration. The SDSI is tightly scheduled in the hierarchical WSN, and its performance is experimentally verified in a laboratory test using a 5-story shear building model. PMID:25856325

  12. Adaptive Mesh Refinement in Curvilinear Body-Fitted Grid Systems

    NASA Technical Reports Server (NTRS)

    Steinthorsson, Erlendur; Modiano, David; Colella, Phillip

    1995-01-01

    To be truly compatible with structured grids, an AMR algorithm should employ a block structure for the refined grids to allow flow solvers to take advantage of the strengths of unstructured grid systems, such as efficient solution algorithms for implicit discretizations and multigrid schemes. One such algorithm, the AMR algorithm of Berger and Colella, has been applied to and adapted for use with body-fitted structured grid systems. Results are presented for a transonic flow over a NACA0012 airfoil (AGARD-03 test case) and a reflection of a shock over a double wedge.

  13. Adaptive mesh refinement in curvilinear body-fitted grid systems

    NASA Astrophysics Data System (ADS)

    Steinthorsson, Erlendur; Modiano, David; Colella, Phillip

    1995-10-01

    To be truly compatible with structured grids, an AMR algorithm should employ a block structure for the refined grids to allow flow solvers to take advantage of the strengths of unstructured grid systems, such as efficient solution algorithms for implicit discretizations and multigrid schemes. One such algorithm, the AMR algorithm of Berger and Colella, has been applied to and adapted for use with body-fitted structured grid systems. Results are presented for a transonic flow over a NACA0012 airfoil (AGARD-03 test case) and a reflection of a shock over a double wedge.

  14. An experimental study of a hybrid adaptive control system

    NASA Technical Reports Server (NTRS)

    Lizewski, E. F.; Monopoli, R. V.

    1974-01-01

    A Liapunov type model reference adaptive control system with five adjustable gains is implemented using a PDP-11 digital computer and an EAI 380 analog computer. The plant controlled is a laboratory type dc servo system. It is made to follow closely a second order linear model. The experimental results demonstrate the feasibility of implementing this rather complex design using only a minicomputer and a reasonable number of operational amplifiers. Also, it points out that satisfactory performance can be achieved even when certain assumptions necessary for the theory are not satisfied.

  15. ISAARE: Information System for Adaptive, Assistive, and Recreational Equipment: Volume I: Existence; Volume II, Communication; Volume V, Adaptation.

    ERIC Educational Resources Information Center

    Melichar, Joseph F.

    Described as part of the Information System for Adaptive, Assistive and Recreational Equipment are equipment items for physically handicapped pupils in the functional areas of existence, equipment and adaptation. Reviewed in the existence section are such items as assistive food containers and container stabilizers, feeder accessories, bowel and…

  16. [Incorporation and adaptation of the postmodern belief system].

    PubMed

    Garzón Pérez, Adela

    2012-01-01

    Every society develops a particular system of beliefs that summarizes its vision of socio-political organization, culture and interpersonal relationships. Each of these three basic dimensions has different forms, depending on the spatial and temporal context of societies. The belief system of the service societies is characterized by a democratic vision of social and political organization, rejection of radical social changes and high levels of interpersonal trust. This paper empirically examines the incorporation and adaptation of the postmodern belief system in a sample of university students. The participants belong to a country that is slowly integrating into the service societies. We used a scale of postmodernity to analyze the incorporation of the postmodern belief system. The results indicate that there is a peculiar combination of the three basic dimensions of the postmodern belief system, where the postmodern conceptions of culture and social relationships have lower acceptance.

  17. Identification of open quantum systems from observable time traces

    DOE PAGES

    Zhang, Jun; Sarovar, Mohan

    2015-05-27

    Estimating the parameters that dictate the dynamics of a quantum system is an important task for quantum information processing and quantum metrology, as well as fundamental physics. In our paper we develop a method for parameter estimation for Markovian open quantum systems using a temporal record of measurements on the system. Furthermore, the method is based on system realization theory and is a generalization of our previous work on identification of Hamiltonian parameters.

  18. Identification of dynamical biological systems based on random effects models.

    PubMed

    Batista, Levy; Bastogne, Thierry; Djermoune, El-Hadi

    2015-01-01

    System identification is a data-driven modeling approach more and more used in biology and biomedicine. In this application context, each assay is always repeated to estimate the response variability. The inference of the modeling conclusions to the whole population requires to account for the inter-individual variability within the modeling procedure. One solution consists in using random effects models but up to now no similar approach exists in the field of dynamical system identification. In this article, we propose a new solution based on an ARX (Auto Regressive model with eXternal inputs) structure using the EM (Expectation-Maximisation) algorithm for the estimation of the model parameters. Simulations show the relevance of this solution compared with a classical procedure of system identification repeated for each subject. PMID:26736981

  19. Numerical studies of identification in nonlinear distributed parameter systems

    NASA Technical Reports Server (NTRS)

    Banks, H. T.; Lo, C. K.; Reich, Simeon; Rosen, I. G.

    1989-01-01

    An abstract approximation framework and convergence theory for the identification of first and second order nonlinear distributed parameter systems developed previously by the authors and reported on in detail elsewhere are summarized and discussed. The theory is based upon results for systems whose dynamics can be described by monotone operators in Hilbert space and an abstract approximation theorem for the resulting nonlinear evolution system. The application of the theory together with numerical evidence demonstrating the feasibility of the general approach are discussed in the context of the identification of a first order quasi-linear parabolic model for one dimensional heat conduction/mass transport and the identification of a nonlinear dissipation mechanism (i.e., damping) in a second order one dimensional wave equation. Computational and implementational considerations, in particular, with regard to supercomputing, are addressed.

  20. Adaptive-passive vibration control systems for industrial applications

    NASA Astrophysics Data System (ADS)

    Mayer, D.; Pfeiffer, T.; Vrbata, J.; Melz, T.

    2015-04-01

    Tuned vibration absorbers have become common for passive vibration reduction in many industrial applications. Lightly damped absorbers (also called neutralizers) can be used to suppress narrowband disturbances by tuning them to the excitation frequency. If the resonance is adapted in-operation, the performance of those devices can be significantly enhanced, or inertial mass can be decreased. However, the integration of actuators, sensors and control electronics into the system raises new design challenges. In this work, the development of adaptive-passive systems for vibration reduction at an industrial scale is presented. As an example, vibration reduction of a ship engine was studied in a full scale test. Simulations were used to study the feasibility and evaluate the system concept at an early stage. Several ways to adjust the resonance of the neutralizer were evaluated, including piezoelectric actuation and common mechatronic drives. Prototypes were implemented and tested. Since vibration absorbers suffer from high dynamic loads, reliability tests were used to assess the long-term behavior under operational conditions and to improve the components. It was proved that the adaptive systems are capable to withstand the mechanical loads in an industrial application. Also a control strategy had to be implemented in order to track the excitation frequency. The most mature concepts were integrated into the full scale test. An imbalance exciter was used to simulate the engine vibrations at a realistic level experimentally. The neutralizers were tested at varying excitation frequencies to evaluate the tracking capabilities of the control system. It was proved that a significant vibration reduction is possible.

  1. Fuzzy Adaptive Cubature Kalman Filter for Integrated Navigation Systems.

    PubMed

    Tseng, Chien-Hao; Lin, Sheng-Fuu; Jwo, Dah-Jing

    2016-01-01

    This paper presents a sensor fusion method based on the combination of cubature Kalman filter (CKF) and fuzzy logic adaptive system (FLAS) for the integrated navigation systems, such as the GPS/INS (Global Positioning System/inertial navigation system) integration. The third-degree spherical-radial cubature rule applied in the CKF has been employed to avoid the numerically instability in the system model. In processing navigation integration, the performance of nonlinear filter based estimation of the position and velocity states may severely degrade caused by modeling errors due to dynamics uncertainties of the vehicle. In order to resolve the shortcoming for selecting the process noise covariance through personal experience or numerical simulation, a scheme called the fuzzy adaptive cubature Kalman filter (FACKF) is presented by introducing the FLAS to adjust the weighting factor of the process noise covariance matrix. The FLAS is incorporated into the CKF framework as a mechanism for timely implementing the tuning of process noise covariance matrix based on the information of degree of divergence (DOD) parameter. The proposed FACKF algorithm shows promising accuracy improvement as compared to the extended Kalman filter (EKF), unscented Kalman filter (UKF), and CKF approaches. PMID:27472336

  2. Fuzzy Adaptive Cubature Kalman Filter for Integrated Navigation Systems

    PubMed Central

    Tseng, Chien-Hao; Lin, Sheng-Fuu; Jwo, Dah-Jing

    2016-01-01

    This paper presents a sensor fusion method based on the combination of cubature Kalman filter (CKF) and fuzzy logic adaptive system (FLAS) for the integrated navigation systems, such as the GPS/INS (Global Positioning System/inertial navigation system) integration. The third-degree spherical-radial cubature rule applied in the CKF has been employed to avoid the numerically instability in the system model. In processing navigation integration, the performance of nonlinear filter based estimation of the position and velocity states may severely degrade caused by modeling errors due to dynamics uncertainties of the vehicle. In order to resolve the shortcoming for selecting the process noise covariance through personal experience or numerical simulation, a scheme called the fuzzy adaptive cubature Kalman filter (FACKF) is presented by introducing the FLAS to adjust the weighting factor of the process noise covariance matrix. The FLAS is incorporated into the CKF framework as a mechanism for timely implementing the tuning of process noise covariance matrix based on the information of degree of divergence (DOD) parameter. The proposed FACKF algorithm shows promising accuracy improvement as compared to the extended Kalman filter (EKF), unscented Kalman filter (UKF), and CKF approaches. PMID:27472336

  3. Active reflective components for adaptive optical zoom systems

    NASA Astrophysics Data System (ADS)

    Jungwirth, Matthew Edward Lewis

    This dissertation presents the theoretical and experimental exploration of active reflective components specifically for large-aperture adaptive optical zoom systems. An active reflective component can change its focal length by physically deforming its reflecting surface. Adaptive optical zoom (AOZ) utilizes active components in order to change magnification and achieve optical zoom, as opposed to traditional zooming systems that move elements along the optical axis. AOZ systems are theoretically examined using a novel optical design theory that enables a full-scale tradespace analysis, where optical design begins from a broad perspective and optimizes to a particular system. The theory applies existing strategies for telescope design and aberration simulation to AOZ, culminating in the design of a Cassegrain objective with a 3.3X zoom ratio and a 375mm entrance aperture. AOZ systems are experimentally examined with the development of a large-aperture active mirror constructed of a composite material called carbon fiber reinforced polymer (CFRP). The active CFRP mirror uses a novel actuation method to change radius of curvature, where actuators press against two annular rings placed on the mirror's back. This method enables the radius of curvature to increase from 2000mm to 2010mm. Closed-loop control maintains good optical performance of 1.05 waves peak-to-valley (with respect to a HeNe laser) when the active CFRP mirror is used in conjunction with a commercial deformable mirror.

  4. Fuzzy Adaptive Cubature Kalman Filter for Integrated Navigation Systems.

    PubMed

    Tseng, Chien-Hao; Lin, Sheng-Fuu; Jwo, Dah-Jing

    2016-07-26

    This paper presents a sensor fusion method based on the combination of cubature Kalman filter (CKF) and fuzzy logic adaptive system (FLAS) for the integrated navigation systems, such as the GPS/INS (Global Positioning System/inertial navigation system) integration. The third-degree spherical-radial cubature rule applied in the CKF has been employed to avoid the numerically instability in the system model. In processing navigation integration, the performance of nonlinear filter based estimation of the position and velocity states may severely degrade caused by modeling errors due to dynamics uncertainties of the vehicle. In order to resolve the shortcoming for selecting the process noise covariance through personal experience or numerical simulation, a scheme called the fuzzy adaptive cubature Kalman filter (FACKF) is presented by introducing the FLAS to adjust the weighting factor of the process noise covariance matrix. The FLAS is incorporated into the CKF framework as a mechanism for timely implementing the tuning of process noise covariance matrix based on the information of degree of divergence (DOD) parameter. The proposed FACKF algorithm shows promising accuracy improvement as compared to the extended Kalman filter (EKF), unscented Kalman filter (UKF), and CKF approaches.

  5. Agent Technology, Complex Adaptive Systems, and Autonomic Systems: Their Relationships

    NASA Technical Reports Server (NTRS)

    Truszkowski, Walt; Rash, James; Rouff, Chistopher; Hincheny, Mike

    2004-01-01

    To reduce the cost of future spaceflight missions and to perform new science, NASA has been investigating autonomous ground and space flight systems. These goals of cost reduction have been further complicated by nanosatellites for future science data-gathering which will have large communications delays and at times be out of contact with ground control for extended periods of time. This paper describes two prototype agent-based systems, the Lights-out Ground Operations System (LOGOS) and the Agent Concept Testbed (ACT), and their autonomic properties that were developed at NASA Goddard Space Flight Center (GSFC) to demonstrate autonomous operations of future space flight missions. The paper discusses the architecture of the two agent-based systems, operational scenarios of both, and the two systems autonomic properties.

  6. [Cross-cultural adaptation of the Vulnerable Elders Survey-13 (VES-13): helping in the identification of vulnerable older people].

    PubMed

    Maia, Flávia de Oliveira Motta; Duarte, Yeda Aparecida de Oliveira; Secoli, Silvia Regina; Santos, Jair Lício Ferreira; Lebrão, Maria Lúcia

    2012-10-01

    To use the VES-13 a tool for identifying vulnerable older people cultural adaptation was performed, a process that seeks the equivalence between the original instrument and its version in another culture. The evaluation of semantic, idiomatic, cultural and conceptual equivalence obtained a general average agreement of 78%, 78%, 97.0% and 94.0% respectively. Kappa coefficient was used to verify the agreement in test-retest reliability, where variables were significant. The analysis of internal consistency was measured by using Cronbach's alpha coefficient, where 70% of the phenomenon under study are represented in the VES-13. The VES-13, translated and adapted, is a reliable instrument with respect to stability and internal consistency of their measurements. Its simple structure and easy to use may therefore contribute to the identification of vulnerable older people, thus contributing to the prioritization of monitoring health services.

  7. Adaptive Systems Engineering: A Medical Paradigm for Practicing Systems Engineering

    SciTech Connect

    R. Douglas Hamelin; Ron D. Klingler; Christopher Dieckmann

    2011-06-01

    From its inception in the defense and aerospace industries, SE has applied holistic, interdisciplinary tools and work-process to improve the design and management of 'large, complex engineering projects.' The traditional scope of engineering in general embraces the design, development, production, and operation of physical systems, and SE, as originally conceived, falls within that scope. While this 'traditional' view has expanded over the years to embrace wider, more holistic applications, much of the literature and training currently available is still directed almost entirely at addressing the large, complex, NASA and defense-sized systems wherein the 'ideal' practice of SE provides the cradle-to-grave foundation for system development and deployment. Under such scenarios, systems engineers are viewed as an integral part of the system and project life-cycle from conception to decommissioning. In far less 'ideal' applications, SE principles are equally applicable to a growing number of complex systems and projects that need to be 'rescued' from overwhelming challenges that threaten imminent failure. The medical profession provides a unique analogy for this latter concept and offers a useful paradigm for tailoring our 'practice' of SE to address the unexpected dynamics of applying SE in the real world. In short, we can be much more effective as systems engineers as we change some of the paradigms under which we teach and 'practice' SE.

  8. Modeling and Identification of a Large Gap Magnetic Suspension System

    NASA Technical Reports Server (NTRS)

    Cox, David E. (Editor); Groom, Nelson J. (Editor); Hsiao, Min-Hung; Huang, Jen-Kuang

    1996-01-01

    This paper presents the results of modeling and system identification efforts on the NASA Large-Angle Magnetic Suspension Test Fixture (LAMSTF). The LAMSTF consists of a cylindrical permanent magnet which is levitated above a planar array of five electromagnets mounted in a circular configuration. The analytical model is first developed and open-loop characteristics are described. The system is shown to be highly unstable and requires feedback control in order to apply system identification. Limitations on modeling accuracy due to the effect of eddy-currents on the system are discussed. An algorithm is derived to identify a state-space model for the system from input/output data acquired during closed-loop operation. The algorithm is tested on both the baseline system and a perturbed system which has an increased presence of eddy currents. It is found that for the baseline system the analytic model adequately captures the dynamics, although the identified model improves the simulation accuracy. For the system perturbed by additional unmodeled eddy-currents the analytic model is no longer adequate and a higher-order model, determined through system identification, is required to accurately predict the system's time response.

  9. Immune System Toxicity and Immunotoxicity Hazard Identification

    EPA Science Inventory

    Exposure to chemicals may alter immune system health, increasing the risk of infections, allergy and autoimmune diseases. The chapter provides a concise overview of the immune system, host factors that affect immune system heal, and the effects that xenobiotic exposure may have ...

  10. Dual-phase evolution in complex adaptive systems

    PubMed Central

    Paperin, Greg; Green, David G.; Sadedin, Suzanne

    2011-01-01

    Understanding the origins of complexity is a key challenge in many sciences. Although networks are known to underlie most systems, showing how they contribute to well-known phenomena remains an issue. Here, we show that recurrent phase transitions in network connectivity underlie emergent phenomena in many systems. We identify properties that are typical of systems in different connectivity phases, as well as characteristics commonly associated with the phase transitions. We synthesize these common features into a common framework, which we term dual-phase evolution (DPE). Using this framework, we review the literature from several disciplines to show that recurrent connectivity phase transitions underlie the complex properties of many biological, physical and human systems. We argue that the DPE framework helps to explain many complex phenomena, including perpetual novelty, modularity, scale-free networks and criticality. Our review concludes with a discussion of the way DPE relates to other frameworks, in particular, self-organized criticality and the adaptive cycle. PMID:21247947

  11. Fourier transform digital holographic adaptive optics imaging system

    PubMed Central

    Liu, Changgeng; Yu, Xiao; Kim, Myung K.

    2013-01-01

    A Fourier transform digital holographic adaptive optics imaging system and its basic principles are proposed. The CCD is put at the exact Fourier transform plane of the pupil of the eye lens. The spherical curvature introduced by the optics except the eye lens itself is eliminated. The CCD is also at image plane of the target. The point-spread function of the system is directly recorded, making it easier to determine the correct guide-star hologram. Also, the light signal will be stronger at the CCD, especially for phase-aberration sensing. Numerical propagation is avoided. The sensor aperture has nothing to do with the resolution and the possibility of using low coherence or incoherent illumination is opened. The system becomes more efficient and flexible. Although it is intended for ophthalmic use, it also shows potential application in microscopy. The robustness and feasibility of this compact system are demonstrated by simulations and experiments using scattering objects. PMID:23262541

  12. System identification and the modeling of sailing yachts

    NASA Astrophysics Data System (ADS)

    Legursky, Katrina

    yaw. Existing aerodynamic models for sailing yachts are unsuitable for control system design as they do not include a physical description of the sails' dynamic effect on the system. A new aerodynamic model is developed and validated using the full-scale sailing data which includes sail deflection as a control input to the system. The Maximum Likelihood Estimation (MLE) algorithm is used with non-linear simulation data to successfully estimate a set of hydrodynamic derivatives for a sailing yacht. It is shown that all sailing yacht models will contain a second order mode (referred to herein as Mode 1A.S or 4B.S) which is dependent upon trimmed roll angle. For the test yacht it is concluded that for this mode when the trimmed roll angle is, roll rate and roll angle are the dominant motion variables, and for surge velocity and yaw rate dominate. This second order mode is dynamically stable for . It transitions from stability in the higher values of to instability in the region defined by. These conclusions align with other work which has also found roll angle to be a driving factor in the dynamic behavior of a tall-ship (Johnson, Miles, Lasher, & Womack, 2009). It is also shown that all linear models also contain a first order mode, (referred to herein as Mode 3A.F or 1B.F), which lies very close to the origin of the complex plane indicating a long time constant. Measured models have indicated this mode can be stable or unstable. The eigenvector analysis reveals that the mode is stable if the surge contribution is < 40% and the sway contribution is > 20%. The small set of maneuvers necessary for model identification, quick OSLS estimation method, and detailed modal analysis of estimated models outlined in this work are immediately applicable to existing autonomous mono-hull sailing yachts, and could readily be adapted for use with other wind-powered vessel configurations such as wing-sails, catamarans, and tri-marans. (Abstract shortened by UMI.)

  13. Modeling electrostrictive deformable mirrors in adaptive optics systems

    NASA Astrophysics Data System (ADS)

    Hom, Craig L.; Dean, Peter D.; Winzer, Stephen R.

    2000-06-01

    Adaptive optics correct light wavefront distortion caused by atmospheric turbulence or internal heating of optical components. This distortion often limits performance in ground-based astronomy, space-based earth observation and high energy laser applications. The heart of the adaptive optics system is the deformable mirror. In this study, an electromechanical model of a deformable mirror was developed as a design tool. The model consisted of a continuous, mirrored face sheet driven with multilayered, electrostrictive actuators. A fully coupled constitutive law simulated the nonlinear, electromechanical behavior of the actuators, while finite element computations determined the mirror's mechanical stiffness observed by the array. Static analysis of the mirror/actuator system related different electrical inputs to the array with the deformation of the mirrored surface. The model also examined the nonlinear influence of internal stresses on the active array's electromechanical performance and quantified crosstalk between neighboring elements. The numerical predictions of the static version of the model agreed well with experimental measurements made on an actual mirror system. The model was also used to simulate the systems level performance of a deformable mirror correcting a thermally bloomed laser beam. The nonlinear analysis determined the commanded actuator voltages required for the phase compensation and the resulting wavefront error.

  14. Laser adaptive holographic system for microweighing of nanoobjects

    SciTech Connect

    Romashko, R V; Efimov, T A; Kul'chin, Yu N

    2014-03-28

    A system for measuring the mass of micro- and nanoobjects based on resonance microweighing using the principles of adaptive holographic interferometry is proposed and experimentally implemented. The sensitive element of the system is a microcantilever to which the objects to be weighted are attached. The eigenoscillations of the microcantilever are excited with a laser pulse. The detection of oscillations is implemented using the adaptive holographic interferometer, the key element of which, the dynamic hologram, is formed in the photorefractive crystal CdTe. The detected variation in mass of the particles, attached to the microcantilever, amounted to (420 ± 9) × 10{sup -12} g, the measurement error being 8.5 × 10{sup -12} g. The sensitivity of the measurement system is 1.7 × 10{sup -12} Hz g{sup -1}. The possibility of increasing the sensitivity of the system by 6.5 × 10{sup 6} times and reducing the mass detection threshold by 1.5 × 10{sup 7} times by microcantilevers of submicron size is experimentally demonstrated. (nanoobjects)

  15. Music identification system using MPEG-7 audio signature descriptors.

    PubMed

    You, Shingchern D; Chen, Wei-Hwa; Chen, Woei-Kae

    2013-01-01

    This paper describes a multiresolution system based on MPEG-7 audio signature descriptors for music identification. Such an identification system may be used to detect illegally copied music circulated over the Internet. In the proposed system, low-resolution descriptors are used to search likely candidates, and then full-resolution descriptors are used to identify the unknown (query) audio. With this arrangement, the proposed system achieves both high speed and high accuracy. To deal with the problem that a piece of query audio may not be inside the system's database, we suggest two different methods to find the decision threshold. Simulation results show that the proposed method II can achieve an accuracy of 99.4% for query inputs both inside and outside the database. Overall, it is highly possible to use the proposed system for copyright control. PMID:23533359

  16. Music Identification System Using MPEG-7 Audio Signature Descriptors

    PubMed Central

    You, Shingchern D.; Chen, Wei-Hwa; Chen, Woei-Kae

    2013-01-01

    This paper describes a multiresolution system based on MPEG-7 audio signature descriptors for music identification. Such an identification system may be used to detect illegally copied music circulated over the Internet. In the proposed system, low-resolution descriptors are used to search likely candidates, and then full-resolution descriptors are used to identify the unknown (query) audio. With this arrangement, the proposed system achieves both high speed and high accuracy. To deal with the problem that a piece of query audio may not be inside the system's database, we suggest two different methods to find the decision threshold. Simulation results show that the proposed method II can achieve an accuracy of 99.4% for query inputs both inside and outside the database. Overall, it is highly possible to use the proposed system for copyright control. PMID:23533359

  17. A network identity authentication system based on Fingerprint identification technology

    NASA Astrophysics Data System (ADS)

    Xia, Hong-Bin; Xu, Wen-Bo; Liu, Yuan

    2005-10-01

    Fingerprint verification is one of the most reliable personal identification methods. However, most of the automatic fingerprint identification system (AFIS) is not run via Internet/Intranet environment to meet today's increasing Electric commerce requirements. This paper describes the design and implementation of the archetype system of identity authentication based on fingerprint biometrics technology, and the system can run via Internet environment. And in our system the COM and ASP technology are used to integrate Fingerprint technology with Web database technology, The Fingerprint image preprocessing algorithms are programmed into COM, which deployed on the internet information server. The system's design and structure are proposed, and the key points are discussed. The prototype system of identity authentication based on Fingerprint have been successfully tested and evaluated on our university's distant education applications in an internet environment.

  18. Flight test planning and parameter extraction for rotorcraft system identification

    NASA Technical Reports Server (NTRS)

    Wang, J. C.; Demiroz, M. Y.; Talbot, P. D.

    1986-01-01

    The present study is concerned with the mathematical modelling of aircraft dynamics on the basis of an investigation conducted with the aid of the Rotor System Research Aircraft (RSRA). The particular characteristics of RSRA make it possible to investigate aircraft properties which cannot be readily studied elsewhere, for example in the wind tunnel. The considered experiment had mainly the objective to develop an improved understanding of the physics of rotor flapping dynamics and rotor loads in maneuvers. The employed approach is based on a utilization of parameter identification methodology (PID) with application to helicopters. A better understanding of the contribution of the main rotor to the overall aircraft forces and moments is also to be obtained. Attention is given to the mathematical model of a rotorcraft system, an integrated identification method, flight data processing, and the identification of RSRA mathematical models.

  19. Investigation of an expert systems approach to bacterial identification.

    PubMed

    Brammer, R J; Bryant, T N; May, J H

    1991-10-01

    An investigation was carried out to assess the feasibility of using an expert systems approach to assist in the identification of unknown isolates of bacteria. A system was developed using Lisp which utilized the knowledge stored in standard bacteriological texts. A comparison of the expert systems approach and the probabilistic approach based on Bayes Theorem was made together with the advantages and disadvantages of each approach. PMID:1747777

  20. Climate change adaptation for the US National Wildlife Refuge System

    USGS Publications Warehouse

    Griffith, Brad; Scott, J. Michael; Adamcik, Robert S.; Ashe, Daniel; Czech, Brian; Fischman, Robert; Gonzalez, Patrick; Lawler, Joshua J.; McGuire, A. David; Pidgorna, Anna

    2009-01-01

    Since its establishment in 1903, the National Wildlife Refuge System (NWRS) has grown to 635 units and 37 Wetland Management Districts in the United States and its territories. These units provide the seasonal habitats necessary for migratory waterfowl and other species to complete their annual life cycles. Habitat conversion and fragmentation, invasive species, pollution, and competition for water have stressed refuges for decades, but the interaction of climate change with these stressors presents the most recent, pervasive, and complex conservation challenge to the NWRS. Geographic isolation and small unit size compound the challenges of climate change, but a combined emphasis on species that refuges were established to conserve and on maintaining biological integrity, diversity, and environmental health provides the NWRS with substantial latitude to respond. Individual symptoms of climate change can be addressed at the refuge level, but the strategic response requires system-wide planning. A dynamic vision of the NWRS in a changing climate, an explicit national strategic plan to implement that vision, and an assessment of representation, redundancy, size, and total number of units in relation to conservation targets are the first steps toward adaptation. This adaptation must begin immediately and be built on more closely integrated research and management. Rigorous projections of possible futures are required to facilitate adaptation to change. Furthermore, the effective conservation footprint of the NWRS must be increased through land acquisition, creative partnerships, and educational programs in order for the NWRS to meet its legal mandate to maintain the biological integrity, diversity, and environmental health of the system and the species and ecosystems that it supports.

  1. Climate change adaptation for the US National Wildlife Refuge System.

    PubMed

    Griffith, Brad; Scott, J Michael; Adamcik, Robert; Ashe, Daniel; Czech, Brian; Fischman, Robert; Gonzalez, Patrick; Lawler, Joshua; McGuire, A David; Pidgorna, Anna

    2009-12-01

    Since its establishment in 1903, the National Wildlife Refuge System (NWRS) has grown to 635 units and 37 Wetland Management Districts in the United States and its territories. These units provide the seasonal habitats necessary for migratory waterfowl and other species to complete their annual life cycles. Habitat conversion and fragmentation, invasive species, pollution, and competition for water have stressed refuges for decades, but the interaction of climate change with these stressors presents the most recent, pervasive, and complex conservation challenge to the NWRS. Geographic isolation and small unit size compound the challenges of climate change, but a combined emphasis on species that refuges were established to conserve and on maintaining biological integrity, diversity, and environmental health provides the NWRS with substantial latitude to respond. Individual symptoms of climate change can be addressed at the refuge level, but the strategic response requires system-wide planning. A dynamic vision of the NWRS in a changing climate, an explicit national strategic plan to implement that vision, and an assessment of representation, redundancy, size, and total number of units in relation to conservation targets are the first steps toward adaptation. This adaptation must begin immediately and be built on more closely integrated research and management. Rigorous projections of possible futures are required to facilitate adaptation to change. Furthermore, the effective conservation footprint of the NWRS must be increased through land acquisition, creative partnerships, and educational programs in order for the NWRS to meet its legal mandate to maintain the biological integrity, diversity, and environmental health of the system and the species and ecosystems that it supports.

  2. Robust nonlinear system identification using neural-network models.

    PubMed

    Lu, S; Basar, T

    1998-01-01

    We study the problem of identification for nonlinear systems in the presence of unknown driving noise, using both feedforward multilayer neural network and radial basis function network models. Our objective is to resolve the difficulty associated with the persistency of excitation condition inherent to the standard schemes in the neural identification literature. This difficulty is circumvented here by a novel formulation and by using a new class of identification algorithms recently obtained by Didinsky et al. We show how these algorithms can be exploited to successfully identify the nonlinearity in the system using neural-network models. By embedding the original problem in one with noise-perturbed state measurements, we present a class of identifiers (under L1 and L2 cost criteria) which secure a good approximant for the system nonlinearity provided that some global optimization technique is used. In this respect, many available learning algorithms in the current neural-network literature, e.g., the backpropagation scheme and the genetic algorithms-based scheme, with slight modifications, can ensure the identification of the system nonlinearity. Subsequently, we address the same problem under a third, worst case L(infinity) criterion for an RBF modeling. We present a neural-network version of an H(infinity)-based identification algorithm from Didinsky et al and show how, along with an appropriate choice of control input to enhance excitation, under both full-state-derivative information (FSDI) and noise-perturbed full-state-information (NPFSI), it leads to satisfaction of a relevant persistency of excitation condition, and thereby to robust identification of the nonlinearity. Results from several simulation studies have been included to demonstrate the effectiveness of these algorithms.

  3. Vasodilator factors in the systemic and local adaptations to pregnancy

    PubMed Central

    Valdes, Gloria; Kaufmann, Peter; Corthorn, Jenny; Erices, Rafaela; Brosnihan, K Bridget; Joyner-Grantham, JaNae

    2009-01-01

    We postulate that an orchestrated network composed of various vasodilatory systems participates in the systemic and local hemodynamic adaptations in pregnancy. The temporal patterns of increase in the circulating and urinary levels of five vasodilator factors/systems, prostacyclin, nitric oxide, kallikrein, angiotensin-(1–7) and VEGF, in normal pregnant women and animals, as well as the changes observed in preeclamptic pregnancies support their functional role in maintaining normotension by opposing the vasoconstrictor systems. In addition, the expression of these vasodilators in the different trophoblastic subtypes in various species supports their role in the transformation of the uterine arteries. Moreover, their expression in the fetal endothelium and in the syncytiotrophoblast in humans, rats and guinea-pigs, favour their participation in maintaining the uteroplacental circulation. The findings that sustain the functional associations of the various vasodilators, and their participation by endocrine, paracrine and autocrine regulation of the systemic and local vasoactive changes of pregnancy are abundant and compelling. However, further elucidation of the role of the various players is hampered by methodological problems. Among these difficulties is the complexity of the interactions between the different factors, the likelihood that experimental alterations induced in one system may be compensated by the other players of the network, and the possibility that data obtained by manipulating single factors in vitro or in animal studies may be difficult to translate to the human. In addition, the impossibility of sampling the uteroplacental interface along normal pregnancy precludes obtaining longitudinal profiles of the various players. Nevertheless, the possibility of improving maternal blood pressure regulation, trophoblast invasion and uteroplacental flow by enhancing vasodilation (e.g. L-arginine, NO donors, VEGF transfection) deserves unravelling the

  4. Application of neural adaptive power system stabilizer in a multi-machine power system

    SciTech Connect

    Shamsollahi, P.; Malik, O.P.

    1999-09-01

    Application of a neural adaptive power system stabilizer (NAPSS) to a five-machine power system is described in this paper. The proposed NAPSS comprises two subnetworks. The adaptive neuro-identifier (ANI) to dynamically identify the non-linear plant, and the adaptive neuro-controller (ANC) to damp output oscillations. The back-propagation training method is used on-line to train these subnetworks. The effectiveness of the proposed NAPSS in damping both local and inter-area modes of oscillations and its self-coordination ability are demonstrated.

  5. Reinforcement learning to adaptive control of nonlinear systems.

    PubMed

    Hwang, Kao-Shing; Tan, S W; Tsai, Min-Cheng

    2003-01-01

    Based on the feedback linearization theory, this paper presents how a reinforcement learning scheme that is adopted to construct artificial neural networks (ANNs) can linearize a nonlinear system effectively. The proposed reinforcement linearization learning system (RLLS) consists of two sub-systems: The evaluation predictor (EP) is a long-term policy selector, and the other is a short-term action selector composed of linearizing control (LC) and reinforce predictor (RP) elements. In addition, a reference model plays the role of the environment, which provides the reinforcement signal to the linearizing process. The RLLS thus receives reinforcement signals to accomplish the linearizing behavior to control a nonlinear system such that it can behave similarly to the reference model. Eventually, the RLLS performs identification and linearization concurrently. Simulation results demonstrate that the proposed learning scheme, which is applied to linearizing a pendulum system, provides better control reliability and robustness than conventional ANN schemes. Furthermore, a PI controller is used to control the linearized plant where the affine system behaves like a linear system.

  6. Control of commensal microbiota by the adaptive immune system.

    PubMed

    Zhang, Husen; Luo, Xin M

    2015-01-01

    The symbiotic relationship between the mammalian host and gut microbes has fascinated many researchers in recent years. Use of germ-free animals has contributed to our understanding of how commensal microbes affect the host. Immunodeficiency animals lacking specific components of the mammalian immune system, on the other hand, enable studying of the reciprocal function-how the host controls which microbes to allow for symbiosis. Here we review the recent advances and discuss our perspectives of how to better understand the latter, with an emphasis on the effects of adaptive immunity on the composition and diversity of gut commensal bacteria. PMID:25901893

  7. Performance of the Gemini Planet Imager's adaptive optics system.

    PubMed

    Poyneer, Lisa A; Palmer, David W; Macintosh, Bruce; Savransky, Dmitry; Sadakuni, Naru; Thomas, Sandrine; Véran, Jean-Pierre; Follette, Katherine B; Greenbaum, Alexandra Z; Ammons, S Mark; Bailey, Vanessa P; Bauman, Brian; Cardwell, Andrew; Dillon, Daren; Gavel, Donald; Hartung, Markus; Hibon, Pascale; Perrin, Marshall D; Rantakyrö, Fredrik T; Sivaramakrishnan, Anand; Wang, Jason J

    2016-01-10

    The Gemini Planet Imager's adaptive optics (AO) subsystem was designed specifically to facilitate high-contrast imaging. A definitive description of the system's algorithms and technologies as built is given. 564 AO telemetry measurements from the Gemini Planet Imager Exoplanet Survey campaign are analyzed. The modal gain optimizer tracks changes in atmospheric conditions. Science observations show that image quality can be improved with the use of both the spatially filtered wavefront sensor and linear-quadratic-Gaussian control of vibration. The error budget indicates that for all targets and atmospheric conditions AO bandwidth error is the largest term.

  8. Landsat ecosystem disturbance adaptive processing system (LEDAPS) algorithm description

    USGS Publications Warehouse

    Schmidt, Gail; Jenkerson, Calli; Masek, Jeffrey; Vermote, Eric; Gao, Feng

    2013-01-01

    The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from LandsatThematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product.The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record.This report discusses the LEDAPS algorithm, which was implemented by the USGS.

  9. Chaotic Patterns in Lotka-Volterra Systems with Behavioral Adaptation

    NASA Astrophysics Data System (ADS)

    Lacitignola, D.; Tebaldi, C.

    2006-03-01

    We study the properties of a n2-dimensional Lotka-Volterra system describing competition among species with behaviorally adaptive abilities, in which one species is made ecologically differentiated with respect to the others by carrying capacity and intrinsic growth rate. The case in which one species has a carrying capacity higher than the others is considered here. Stability of equilibria and time-dependent regimes have been investigated in the case of four species: an interesting example of chaotic window and period-adding sequences is presented and discussed.

  10. Context-Aware Adaptation in Web-Based Groupware Systems

    NASA Astrophysics Data System (ADS)

    Pinheiro, Manuele Kirsch; Carrillo-Ramos, Angela; Villanova-Oliver, Marlène; Gensel, Jérôme; Berbers, Yolande

    In this chapter, we propose a context-aware filtering process for adapting content delivered to mobile users by Web-based Groupware Systems. This process is based on context-aware profiles, expressing mobile users preferences for particular situations they encounter when using these systems. These profiles, which are shared between members of a given community, are exploited by the adaptation process in order to select and organize the delivered information into several levels of detail, based on a progressive access model. By defining these profiles, we propose a filtering process that considers both the user's current context and the user's preferences for this context. The context notion of context is represented by an object-oriented model we propose and which takes into account consideration both the user's physical and collaborative context, including elements related to collaborative activities performed inside the groupware system. The filtering process selects, in a first step, the context-aware profiles that match the user's current context, and then it filters the available content according to the selected profiles and uses the progressive access model to organize the selected information.

  11. Introduction to project ALIAS: adaptive-learning image analysis system

    NASA Astrophysics Data System (ADS)

    Bock, Peter

    1992-03-01

    As an alternative to preprogrammed rule-based artificial intelligence, collective learning systems theory postulates a hierarchical network of cellular automata which acquire their knowledge through learning based on a series of trial-and-error interactions with an evaluating environment, much as humans do. The input to the hierarchical network is provided by a set of sensors which perceive the external world. Using both this perceived information and past experience (memory), the learning automata synthesize collections of trial responses, periodically modifying their memories based on internal evaluations or external evaluations from the environment. Based on collective learning systems theory, an adaptive transputer- based image-processing engine comprising a three-layer hierarchical network of 32 learning cells and 33 nonlearning cells has been applied to a difficult image processing task: the scale, phase, and translation-invariant detection of anomalous features in otherwise `normal' images. Known as adaptive learning image analysis system (ALIAS), this parallel-processing engine has been constructed and tested at the Research institute for Applied Knowledge Processing (FAW) in Ulm, Germany under the sponsorship of Robert Bosch GmbH. Results demonstrate excellent detection, discrimination, and localization of anomalies in binary images. Recent enhancements include the ability to process gray-scale images and the automatic supervised segmentation and classification of images. Current research is directed toward the processing of time-series data and the hierarchical extension of ALIAS from the sub-symbolic level to the higher levels of symbolic association.

  12. Adaptive optoelectronic camouflage systems with designs inspired by cephalopod skins

    PubMed Central

    Yu, Cunjiang; Li, Yuhang; Zhang, Xun; Huang, Xian; Malyarchuk, Viktor; Wang, Shuodao; Shi, Yan; Gao, Li; Su, Yewang; Zhang, Yihui; Xu, Hangxun; Hanlon, Roger T.; Huang, Yonggang; Rogers, John A.

    2014-01-01

    Octopus, squid, cuttlefish, and other cephalopods exhibit exceptional capabilities for visually adapting to or differentiating from the coloration and texture of their surroundings, for the purpose of concealment, communication, predation, and reproduction. Long-standing interest in and emerging understanding of the underlying ultrastructure, physiological control, and photonic interactions has recently led to efforts in the construction of artificial systems that have key attributes found in the skins of these organisms. Despite several promising options in active materials for mimicking biological color tuning, existing routes to integrated systems do not include critical capabilities in distributed sensing and actuation. Research described here represents progress in this direction, demonstrated through the construction, experimental study, and computational modeling of materials, device elements, and integration schemes for cephalopod-inspired flexible sheets that can autonomously sense and adapt to the coloration of their surroundings. These systems combine high-performance, multiplexed arrays of actuators and photodetectors in laminated, multilayer configurations on flexible substrates, with overlaid arrangements of pixelated, color-changing elements. The concepts provide realistic routes to thin sheets that can be conformally wrapped onto solid objects to modulate their visual appearance, with potential relevance to consumer, industrial, and military applications. PMID:25136094

  13. Understanding global health governance as a complex adaptive system.

    PubMed

    Hill, Peter S

    2011-01-01

    The transition from international to global health reflects the rapid growth in the numbers and nature of stakeholders in health, as well as the constant change embodied in the process of globalisation itself. This paper argues that global health governance shares the characteristics of complex adaptive systems, with its multiple and diverse players, and their polyvalent and constantly evolving relationships, and rich and dynamic interactions. The sheer quantum of initiatives, the multiple networks through which stakeholders (re)configure their influence, the range of contexts in which development for health is played out - all compound the complexity of this system. This paper maps out the characteristics of complex adaptive systems as they apply to global health governance, linking them to developments in the past two decades, and the multiple responses to these changes. Examining global health governance through the frame of complexity theory offers insight into the current dynamics of governance, and while providing a framework for making meaning of the whole, opens up ways of accessing this complexity through local points of engagement.

  14. Agroforestry Systems In Poland A Preliminary Identification

    NASA Astrophysics Data System (ADS)

    Borek, Robert

    2015-01-01

    This paper seeks to use state-of-the-art knowledge to depict the foundations and prospects for agroforestry systems in Poland to develop, in line with political, legal, historical and environmental conditions pertaining in the country. The main legal provisions concerning the presence of trees in agriculture are presented prior to a first-ever defining of key traditional agroforestry systems in Poland.

  15. System reliability, performance and trust in adaptable automation.

    PubMed

    Chavaillaz, Alain; Wastell, David; Sauer, Jürgen

    2016-01-01

    The present study examined the effects of reduced system reliability on operator performance and automation management in an adaptable automation environment. 39 operators were randomly assigned to one of three experimental groups: low (60%), medium (80%), and high (100%) reliability of automation support. The support system provided five incremental levels of automation which operators could freely select according to their needs. After 3 h of training on a simulated process control task (AutoCAMS) in which the automation worked infallibly, operator performance and automation management were measured during a 2.5-h testing session. Trust and workload were also assessed through questionnaires. Results showed that although reduced system reliability resulted in lower levels of trust towards automation, there were no corresponding differences in the operators' reliance on automation. While operators showed overall a noteworthy ability to cope with automation failure, there were, however, decrements in diagnostic speed and prospective memory with lower reliability.

  16. Neuromorphic adaptive plastic scalable electronics: analog learning systems.

    PubMed

    Srinivasa, Narayan; Cruz-Albrecht, Jose

    2012-01-01

    Decades of research to build programmable intelligent machines have demonstrated limited utility in complex, real-world environments. Comparing their performance with biological systems, these machines are less efficient by a factor of 1 million1 billion in complex, real-world environments. The Systems of Neuromorphic Adaptive Plastic Scalable Electronics (SyNAPSE) program is a multifaceted Defense Advanced Research Projects Agency (DARPA) project that seeks to break the programmable machine paradigm and define a new path for creating useful, intelligent machines. Since real-world systems exhibit infinite combinatorial complexity, electronic neuromorphic machine technology would be preferable in a host of applications, but useful and practical implementations still do not exist. HRL Laboratories LLC has embarked on addressing these challenges, and, in this article, we provide an overview of our project and progress made thus far.

  17. Multifaceted interactions between adaptive immunity and the central nervous system.

    PubMed

    Kipnis, Jonathan

    2016-08-19

    Neuroimmunologists seek to understand the interactions between the central nervous system (CNS) and the immune system, both under homeostatic conditions and in diseases. Unanswered questions include those relating to the diversity and specificity of the meningeal T cell repertoire; the routes taken by immune cells that patrol the meninges under healthy conditions and invade the parenchyma during pathology; the opposing effects (beneficial or detrimental) of these cells on CNS function; the role of immune cells after CNS injury; and the evolutionary link between the two systems, resulting in their tight interaction and interdependence. This Review summarizes the current standing of and challenging questions related to interactions between adaptive immunity and the CNS and considers the possible directions in which these aspects of neuroimmunology will be heading over the next decade. PMID:27540163

  18. Ecosystems and the Biosphere as Complex Adaptive Systems

    NASA Technical Reports Server (NTRS)

    Levin, Simon A.

    1998-01-01

    Ecosystems are prototypical examples of complex adaptive systems, in which patterns at higher levels emerge from localized interactions and selection processes acting at lower levels. An essential aspect of such systems is nonlinearity, leading to historical dependency and multiple possible outcomes of dynamics. Given this, it is essential to determine the degree to which system features are determined by environmental conditions, and the degree to which they are the result of self-organization. Furthermore, given the multiple levels at which dynamics become apparent and at which selection can act, central issues relate to how evolution shapes ecosystems properties, and whether ecosystems become buffered to changes (more resilient) over their ecological and evolutionary development or proceed to critical states and the edge of chaos.

  19. Implementation of modal optimization system of Subaru-188 adaptive optics

    NASA Astrophysics Data System (ADS)

    Hattori, Masayuki; Golota, Taras; Olivier, Guyon; Dinkins, Matthew; Oya, Shin; Colley, Stephen; Eldred, Michael; Watanabe, Makoto; Itoh, Meguru; Saito, Yoshihiko; Hayano, Yutaka; Takami, Hideki; Iye, Masanori

    2006-06-01

    Subaru AO-188 is a curvature adaptive optics system with 188 elements. It has been developed by NAOJ (National Astronomical Observatory of Japan) in recent years, as the upgrade from the existing 36-element AO system currently in operation at Subaru telescope. In this upgrade, the control scheme is also changed from zonal control to modal control. This paper presents development and implementation of the modal optimization system for this new AO-188. Also, we will introduce some special features and attempt in our implementation, such as consideration of resonance of deformable mirror at the lower order modes, and extension of the scheme for the optimization of the magnitude of membrane mirror in wave front sensor. Those are simple but shall be useful enhancement for the better performance to the conservative configuration with conventional modal control, and possibly useful in other extended operation modes or control schemes recently in research and development as well.

  20. Adapting Mars Entry, Descent and Landing System for Earth

    NASA Astrophysics Data System (ADS)

    Heilimo, J.; Harri, A.-M.; Aleksashkin, S.; Koryanov, V.; Guerrero, H.; Schmidt, W.; Haukka, H.; Finchenko, V.; Martynov, M.; Ostresko, B.; Ponomarenko, A.; Kazakovtsev, V.; Arruego, I.; Martin, S.; Siili, T.

    2013-09-01

    In 2001 - 2011 an inflatable Entry, Descent and Landing System (EDLS) for Martian atmosphere was developed by FMI and the MetNet team. This MetNet Mars Lander EDLS is used in both the initial deceleration during atmospheric entry and in the final deceleration before the semi-hard impact of the penetrator to Martian surface. The EDLS design is ingenious and its applicability to Earth's atmosphere is studied in the on-going project. In particular, the behavior of the system in the critical transonic aerodynamic (from hypersonic to subsonic) regime will be investigated. This project targets to analyze and test the transonic behavior of this compact and light weight payload entry system to Earth's atmosphere [1]. Scaling and adaptation for terrestrial atmospheric conditions, instead of a completely new design, is a favorable approach for providing a new re-entry vehicle for terrestrial space applications.

  1. Performance of the Keck Observatory adaptive optics system

    SciTech Connect

    van Dam, M A; Mignant, D L; Macintosh, B A

    2004-01-19

    In this paper, the adaptive optics (AO) system at the W.M. Keck Observatory is characterized. The authors calculate the error budget of the Keck AO system operating in natural guide star mode with a near infrared imaging camera. By modeling the control loops and recording residual centroids, the measurement noise and band-width errors are obtained. The error budget is consistent with the images obtained. Results of sky performance tests are presented: the AO system is shown to deliver images with average Strehl ratios of up to 0.37 at 1.58 {micro}m using a bright guide star and 0.19 for a magnitude 12 star.

  2. System identification requirements for high-bandwidth rotorcraft flight control system design

    NASA Technical Reports Server (NTRS)

    Tischler, Mark B.

    1991-01-01

    The application of system identification methods to high-bandwidth rotorcraft flight control system design is examined. Flight test and modeling requirements are illustrated using flight test data from a BO-105 hingeless rotor helicopter. The proposed approach involves the identification of nonparametric (transfer function and state space) model identification. Results for the BO-105 show the need for including coupled body/rotor flapping and lead-lag dynamics in the identification model structure to allow the accurate prediction of control ssytem bandwidth limitations.

  3. Early identification systems for emerging foodborne hazards.

    PubMed

    Marvin, H J P; Kleter, G A; Prandini, A; Dekkers, S; Bolton, D J

    2009-05-01

    This paper provides a non-exhausting overview of early warning systems for emerging foodborne hazards that are operating in the various places in the world. Special attention is given to endpoint-focussed early warning systems (i.e. ECDC, ISIS and GPHIN) and hazard-focussed early warning systems (i.e. FVO, RASFF and OIE) and their merit to successfully identify a food safety problem in an early stage is discussed. Besides these early warning systems which are based on monitoring of either disease symptoms or hazards, also early warning systems and/or activities that intend to predict the occurrence of a food safety hazard in its very beginning of development or before that are described. Examples are trend analysis, horizon scanning, early warning systems for mycotoxins in maize and/or wheat and information exchange networks (e.g. OIE and GIEWS). Furthermore, recent initiatives that aim to develop predictive early warning systems based on the holistic principle are discussed. The assumption of the researchers applying this principle is that developments outside the food production chain that are either directly or indirectly related to the development of a particular food safety hazard may also provide valuable information to predict the development of this hazard.

  4. Early identification systems for emerging foodborne hazards.

    PubMed

    Marvin, H J P; Kleter, G A; Prandini, A; Dekkers, S; Bolton, D J

    2009-05-01

    This paper provides a non-exhausting overview of early warning systems for emerging foodborne hazards that are operating in the various places in the world. Special attention is given to endpoint-focussed early warning systems (i.e. ECDC, ISIS and GPHIN) and hazard-focussed early warning systems (i.e. FVO, RASFF and OIE) and their merit to successfully identify a food safety problem in an early stage is discussed. Besides these early warning systems which are based on monitoring of either disease symptoms or hazards, also early warning systems and/or activities that intend to predict the occurrence of a food safety hazard in its very beginning of development or before that are described. Examples are trend analysis, horizon scanning, early warning systems for mycotoxins in maize and/or wheat and information exchange networks (e.g. OIE and GIEWS). Furthermore, recent initiatives that aim to develop predictive early warning systems based on the holistic principle are discussed. The assumption of the researchers applying this principle is that developments outside the food production chain that are either directly or indirectly related to the development of a particular food safety hazard may also provide valuable information to predict the development of this hazard. PMID:18272277

  5. 40 CFR 72.33 - Identification of dispatch system.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... (CONTINUED) PERMITS REGULATION Acid Rain Permit Applications § 72.33 Identification of dispatch system. (a... approval of the petition, all provisions of the Acid Rain Program applicable to an affected source or an... provision of the Acid Rain Program and shall not change the liability of the owners and operators of...

  6. 40 CFR 72.33 - Identification of dispatch system.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... (CONTINUED) PERMITS REGULATION Acid Rain Permit Applications § 72.33 Identification of dispatch system. (a... approval of the petition, all provisions of the Acid Rain Program applicable to an affected source or an... provision of the Acid Rain Program and shall not change the liability of the owners and operators of...

  7. 40 CFR 72.33 - Identification of dispatch system.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... (CONTINUED) PERMITS REGULATION Acid Rain Permit Applications § 72.33 Identification of dispatch system. (a... approval of the petition, all provisions of the Acid Rain Program applicable to an affected source or an... provision of the Acid Rain Program and shall not change the liability of the owners and operators of...

  8. 40 CFR 72.33 - Identification of dispatch system.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... (CONTINUED) PERMITS REGULATION Acid Rain Permit Applications § 72.33 Identification of dispatch system. (a... approval of the petition, all provisions of the Acid Rain Program applicable to an affected source or an... provision of the Acid Rain Program and shall not change the liability of the owners and operators of...

  9. 40 CFR 72.33 - Identification of dispatch system.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... (CONTINUED) PERMITS REGULATION Acid Rain Permit Applications § 72.33 Identification of dispatch system. (a... approval of the petition, all provisions of the Acid Rain Program applicable to an affected source or an... provision of the Acid Rain Program and shall not change the liability of the owners and operators of...

  10. Training Sessions Provide Working Knowledge of National Animal Identification System

    ERIC Educational Resources Information Center

    Glaze, J. Benton, Jr.; Ahola, Jason K.

    2010-01-01

    One in-service and two train-the-trainer workshops were conducted by University of Idaho Extension faculty, Idaho State Department of Agriculture personnel, and allied industry representatives to increase Extension educators' knowledge and awareness of the National Animal Identification System (NAIS) and related topics. Training sessions included…

  11. Experimental Simulation of Active Control With On-line System Identification on Sound Transmission Through an Elastic Plate

    NASA Technical Reports Server (NTRS)

    1998-01-01

    An adaptive control algorithm with on-line system identification capability has been developed. One of the great advantages of this scheme is that an additional system identification mechanism such as an additional uncorrelated random signal generator as the source of system identification is not required. A time-varying plate-cavity system is used to demonstrate the control performance of this algorithm. The time-varying system consists of a stainless-steel plate which is bolted down on a rigid cavity opening where the cavity depth was changed with respect to time. For a given externally located harmonic sound excitation, the system identification and the control are simultaneously executed to minimize the transmitted sound in the cavity. The control performance of the algorithm is examined for two cases. First, all the water was drained, the external disturbance frequency is swept with 1 Hz/sec. The result shows an excellent frequency tracking capability with cavity internal sound suppression of 40 dB. For the second case, the water level is initially empty and then raised to 3/20 full in 60 seconds while the external sound excitation is fixed with a frequency. Hence, the cavity resonant frequency decreases and passes the external sound excitation frequency. The algorithm shows 40 dB transmitted noise suppression without compromising the system identification tracking capability.

  12. Optical Design for Extremely Large Telescope Adaptive Optics Systems

    SciTech Connect

    Bauman, B J

    2003-11-26

    Designing an adaptive optics (AO) system for extremely large telescopes (ELT's) will present new optical engineering challenges. Several of these challenges are addressed in this work, including first-order design of multi-conjugate adaptive optics (MCAO) systems, pyramid wavefront sensors (PWFS's), and laser guide star (LGS) spot elongation. MCAO systems need to be designed in consideration of various constraints, including deformable mirror size and correction height. The y,{bar y} method of first-order optical design is a graphical technique that uses a plot with marginal and chief ray heights as coordinates; the optical system is represented as a segmented line. This method is shown to be a powerful tool in designing MCAO systems. From these analyses, important conclusions about configurations are derived. PWFS's, which offer an alternative to Shack-Hartmann (SH) wavefront sensors (WFS's), are envisioned as the workhorse of layer-oriented adaptive optics. Current approaches use a 4-faceted glass pyramid to create a WFS analogous to a quad-cell SH WFS. PWFS's and SH WFS's are compared and some newly-considered similarities and PWFS advantages are presented. Techniques to extend PWFS's are offered: First, PWFS's can be extended to more pixels in the image by tiling pyramids contiguously. Second, pyramids, which are difficult to manufacture, can be replaced by less expensive lenslet arrays. An approach is outlined to convert existing SH WFS's to PWFS's for easy evaluation of PWFS's. Also, a demonstration of PWFS's in sensing varying amounts of an aberration is presented. For ELT's, the finite altitude and finite thickness of LGS's means that the LGS will appear elongated from the viewpoint of subapertures not directly under the telescope. Two techniques for dealing with LGS spot elongation in SH WFS's are presented. One method assumes that the laser will be pulsed and uses a segmented micro-electromechanical system (MEMS) to track the LGS light subaperture by

  13. DNA barcode-based molecular identification system for fish species.

    PubMed

    Kim, Sungmin; Eo, Hae-Seok; Koo, Hyeyoung; Choi, Jun-Kil; Kim, Won

    2010-12-01

    In this study, we applied DNA barcoding to identify species using short DNA sequence analysis. We examined the utility of DNA barcoding by identifying 53 Korean freshwater fish species, 233 other freshwater fish species, and 1339 saltwater fish species. We successfully developed a web-based molecular identification system for fish (MISF) using a profile hidden Markov model. MISF facilitates efficient and reliable species identification, overcoming the limitations of conventional taxonomic approaches. MISF is freely accessible at http://bioinfosys.snu.ac.kr:8080/MISF/misf.jsp .

  14. Space Launch System Implementation of Adaptive Augmenting Control

    NASA Technical Reports Server (NTRS)

    Wall, John H.; Orr, Jeb S.; VanZwieten, Tannen S.

    2014-01-01

    Given the complex structural dynamics, challenging ascent performance requirements, and rigorous flight certification constraints owing to its manned capability, the NASA Space Launch System (SLS) launch vehicle requires a proven thrust vector control algorithm design with highly optimized parameters to provide stable and high-performance flight. On its development path to Preliminary Design Review (PDR), the SLS flight control system has been challenged by significant vehicle flexibility, aerodynamics, and sloshing propellant. While the design has been able to meet all robust stability criteria, it has done so with little excess margin. Through significant development work, an Adaptive Augmenting Control (AAC) algorithm has been shown to extend the envelope of failures and flight anomalies the SLS control system can accommodate while maintaining a direct link to flight control stability criteria such as classical gain and phase margin. In this paper, the work performed to mature the AAC algorithm as a baseline component of the SLS flight control system is presented. The progress to date has brought the algorithm design to the PDR level of maturity. The algorithm has been extended to augment the full SLS digital 3-axis autopilot, including existing load-relief elements, and the necessary steps for integration with the production flight software prototype have been implemented. Several updates which have been made to the adaptive algorithm to increase its performance, decrease its sensitivity to expected external commands, and safeguard against limitations in the digital implementation are discussed with illustrating results. Monte Carlo simulations and selected stressing case results are also shown to demonstrate the algorithm's ability to increase the robustness of the integrated SLS flight control system.

  15. Space Launch System Implementation of Adaptive Augmenting Control

    NASA Technical Reports Server (NTRS)

    VanZwieten, Tannen S.; Wall, John H.; Orr, Jeb S.

    2014-01-01

    Given the complex structural dynamics, challenging ascent performance requirements, and rigorous flight certification constraints owing to its manned capability, the NASA Space Launch System (SLS) launch vehicle requires a proven thrust vector control algorithm design with highly optimized parameters to robustly demonstrate stable and high performance flight. On its development path to preliminary design review (PDR), the stability of the SLS flight control system has been challenged by significant vehicle flexibility, aerodynamics, and sloshing propellant dynamics. While the design has been able to meet all robust stability criteria, it has done so with little excess margin. Through significant development work, an adaptive augmenting control (AAC) algorithm previously presented by Orr and VanZwieten, has been shown to extend the envelope of failures and flight anomalies for which the SLS control system can accommodate while maintaining a direct link to flight control stability criteria (e.g. gain & phase margin). In this paper, the work performed to mature the AAC algorithm as a baseline component of the SLS flight control system is presented. The progress to date has brought the algorithm design to the PDR level of maturity. The algorithm has been extended to augment the SLS digital 3-axis autopilot, including existing load-relief elements, and necessary steps for integration with the production flight software prototype have been implemented. Several updates to the adaptive algorithm to increase its performance, decrease its sensitivity to expected external commands, and safeguard against limitations in the digital implementation are discussed with illustrating results. Monte Carlo simulations and selected stressing case results are shown to demonstrate the algorithm's ability to increase the robustness of the integrated SLS flight control system.

  16. Adaptive optics ophthalmologic systems using dual deformable mirrors

    SciTech Connect

    Jones, S; Olivier, S; Chen, D; Sadda, S; Joeres, S; Zawadzki, R; Werner, J S; Miller, D

    2007-02-01

    Adaptive Optics (AO) have been increasingly combined with a variety of ophthalmic instruments over the last decade to provide cellular-level, in-vivo images of the eye. The use of MEMS deformable mirrors in these instruments has recently been demonstrated to reduce system size and cost while improving performance. However, currently available MEMS mirrors lack the required range of motion for correcting large ocular aberrations, such as defocus and astigmatism. In order to address this problem, we have developed an AO system architecture that uses two deformable mirrors, in a woofer/tweeter arrangement, with a bimorph mirror as the woofer and a MEMS mirror as the tweeter. This setup provides several advantages, including extended aberration correction range, due to the large stroke of the bimorph mirror, high order aberration correction using the MEMS mirror, and additionally, the ability to ''focus'' through the retina. This AO system architecture is currently being used in four instruments, including an Optical Coherence Tomography (OCT) system and a retinal flood-illuminated imaging system at the UC Davis Medical Center, a Scanning Laser Ophthalmoscope (SLO) at the Doheny Eye Institute, and an OCT system at Indiana University. The design, operation and evaluation of this type of AO system architecture will be presented.

  17. Biometric identification systems: the science of transaction facilitation

    NASA Astrophysics Data System (ADS)

    Rogers, Robert R.

    1994-10-01

    The future ofthe "secure transaction" and the success ofall undertakings that depend on absolute certainty that the individuals involved really are who and what they represent themselves to be is dependent upon the successful development of absolutely accurate, low-cost and easy-to-operate Biometric Identification Systems. Whether these transactions are political, military, financial or administrative (e.g. health cards, drivers licenses, welfare entitlement, national identification cards, credit card transactions, etc.), the need for such secure and positive identification has never been greater -and yet we are only at the beginning ofan era in which we will see the emergence and proliferation of Biometric Identification Systems in nearly every field ofhuman endeavor. Proper application ofthese systems will change the way the world operates, and that is precisely the goal ofComparator Systems Corporation. Just as with the photo-copier 40 years ago and the personal computer 20 years ago, the potential applications for positive personal identification are going to make the Biometric Identification System a commonplace component in the standard practice ofbusiness, and in interhuman relationships ofall kinds. The development of new and specific application hardware, as well as the necessary algorithms and related software required for integration into existing operating procedures and newly developed systems alike, has been a more-than-a-decade-long process at Comparator -and we are now on the verge of delivering these systems to the world markets so urgently in need of them. An individual could feel extremely confident and satisfied ifhe could present his credit, debit, or ATM card at any point of sale and, after inserting his card, could simply place his finger on a glass panel and in less than a second be positively accepted as being the person that the card purported him to be; not to mention the security and satisfaction of the vendor involved in knowing that

  18. How a well-adapted immune system is organized

    PubMed Central

    Mayer, Andreas; Balasubramanian, Vijay; Mora, Thierry; Walczak, Aleksandra M.

    2015-01-01

    The repertoire of lymphocyte receptors in the adaptive immune system protects organisms from diverse pathogens. A well-adapted repertoire should be tuned to the pathogenic environment to reduce the cost of infections. We develop a general framework for predicting the optimal repertoire that minimizes the cost of infections contracted from a given distribution of pathogens. The theory predicts that the immune system will have more receptors for rare antigens than expected from the frequency of encounters; individuals exposed to the same infections will have sparse repertoires that are largely different, but nevertheless exploit cross-reactivity to provide the same coverage of antigens; and the optimal repertoires can be reached via the dynamics of competitive binding of antigens by receptors and selective amplification of stimulated receptors. Our results follow from a tension between the statistics of pathogen detection, which favor a broader receptor distribution, and the effects of cross-reactivity, which tend to concentrate the optimal repertoire onto a few highly abundant clones. Our predictions can be tested in high-throughput surveys of receptor and pathogen diversity. PMID:25918407

  19. Integration of AdaptiSPECT, a small-animal adaptive SPECT imaging system

    PubMed Central

    Chaix, Cécile; Kovalsky, Stephen; Kosmider, Matthew; Barrett, Harrison H.; Furenlid, Lars R.

    2015-01-01

    AdaptiSPECT is a pre-clinical adaptive SPECT imaging system under final development at the Center for Gamma-ray Imaging. The system incorporates multiple adaptive features: an adaptive aperture, 16 detectors mounted on translational stages, and the ability to switch between a non-multiplexed and a multiplexed imaging configuration. In this paper, we review the design of AdaptiSPECT and its adaptive features. We then describe the on-going integration of the imaging system. PMID:26347197

  20. Performance metrics for the evaluation of hyperspectral chemical identification systems

    NASA Astrophysics Data System (ADS)

    Truslow, Eric; Golowich, Steven; Manolakis, Dimitris; Ingle, Vinay

    2016-02-01

    Remote sensing of chemical vapor plumes is a difficult but important task for many military and civilian applications. Hyperspectral sensors operating in the long-wave infrared regime have well-demonstrated detection capabilities. However, the identification of a plume's chemical constituents, based on a chemical library, is a multiple hypothesis testing problem which standard detection metrics do not fully describe. We propose using an additional performance metric for identification based on the so-called Dice index. Our approach partitions and weights a confusion matrix to develop both the standard detection metrics and identification metric. Using the proposed metrics, we demonstrate that the intuitive system design of a detector bank followed by an identifier is indeed justified when incorporating performance information beyond the standard detection metrics.

  1. Numerical Experimentation with Maximum Likelihood Identification in Static Distributed Systems

    NASA Technical Reports Server (NTRS)

    Scheid, R. E., Jr.; Rodriguez, G.

    1985-01-01

    Many important issues in the control of large space structures are intimately related to the fundamental problem of parameter identification. One might also ask how well this identification process can be carried out in the presence of noisy data since no sensor system is perfect. With these considerations in mind the algorithms herein are designed to treat both the case of uncertainties in the modeling and uncertainties in the data. The analytical aspects of maximum likelihood identification are considered in some detail in another paper. The questions relevant to the implementation of these schemes are dealt with, particularly as they apply to models of large space structures. The emphasis is on the influence of the infinite dimensional character of the problem on finite dimensional implementations of the algorithms. Those areas of current and future analysis are highlighted which indicate the interplay between error analysis and possible truncations of the state and parameter spaces.

  2. Online adaptive policy learning algorithm for H∞ state feedback control of unknown affine nonlinear discrete-time systems.

    PubMed

    Zhang, Huaguang; Qin, Chunbin; Jiang, Bin; Luo, Yanhong

    2014-12-01

    The problem of H∞ state feedback control of affine nonlinear discrete-time systems with unknown dynamics is investigated in this paper. An online adaptive policy learning algorithm (APLA) based on adaptive dynamic programming (ADP) is proposed for learning in real-time the solution to the Hamilton-Jacobi-Isaacs (HJI) equation, which appears in the H∞ control problem. In the proposed algorithm, three neural networks (NNs) are utilized to find suitable approximations of the optimal value function and the saddle point feedback control and disturbance policies. Novel weight updating laws are given to tune the critic, actor, and disturbance NNs simultaneously by using data generated in real-time along the system trajectories. Considering NN approximation errors, we provide the stability analysis of the proposed algorithm with Lyapunov approach. Moreover, the need of the system input dynamics for the proposed algorithm is relaxed by using a NN identification scheme. Finally, simulation examples show the effectiveness of the proposed algorithm. PMID:25095274

  3. 77 FR 40735 - Unique Device Identification System

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-07-10

    ... intended to be sterilized before each use; and stand-alone software. These types of devices have physical... Systems by Hospitals and Other Healthcare Facilities and on Statistical Methodologies to Interpret the... each use; and Stand-alone software. These devices involve unique risks to patients, and consequently...

  4. Complex adaptive systems and game theory: An unlikely union

    USGS Publications Warehouse

    Hadzikadic, M.; Carmichael, T.; Curtin, C.

    2010-01-01

    A Complex Adaptive System is a collection of autonomous, heterogeneous agents, whose behavior is defined with a limited number of rules. A Game Theory is a mathematical construct that assumes a small number of rational players who have a limited number of actions or strategies available to them. The CAS method has the potential to alleviate some of the shortcomings of GT. On the other hand, CAS researchers are always looking for a realistic way to define interactions among agents. GT offers an attractive option for defining the rules of such interactions in a way that is both potentially consistent with observed real-world behavior and subject to mathematical interpretation. This article reports on the results of an effort to build a CAS system that utilizes GT for determining the actions of individual agents. ?? 2009 Wiley Periodicals, Inc. Complexity, 16,24-42, 2010.

  5. ADGS-2100 Adaptive Display and Guidance System Window Manager Analysis

    NASA Technical Reports Server (NTRS)

    Whalen, Mike W.; Innis, John D.; Miller, Steven P.; Wagner, Lucas G.

    2006-01-01

    Recent advances in modeling languages have made it feasible to formally specify and analyze the behavior of large system components. Synchronous data flow languages, such as Lustre, SCR, and RSML-e are particularly well suited to this task, and commercial versions of these tools such as SCADE and Simulink are growing in popularity among designers of safety critical systems, largely due to their ability to automatically generate code from the models. At the same time, advances in formal analysis tools have made it practical to formally verify important properties of these models to ensure that design defects are identified and corrected early in the lifecycle. This report describes how these tools have been applied to the ADGS-2100 Adaptive Display and Guidance Window Manager being developed by Rockwell Collins Inc. This work demonstrates how formal methods can be easily and cost-efficiently used to remove defects early in the design cycle.

  6. Anisoplanatism in adaptive optics systems due to pupil aberrations

    SciTech Connect

    Bauman, B

    2005-08-01

    Adaptive optics systems typically include an optical relay that simultaneously images the science field to be corrected and also a set of pupil planes conjugate to the deformable mirror of the system. Often, in the optical spaces where DM's are placed, the pupils are aberrated, leading to a displacement and/or distortion of the pupil that varies according to field position--producing a type of anisoplanatism, i.e., a degradation of the AO correction with field angle. The pupil aberration phenomenon is described and expressed in terms of Seidel aberrations. An expression for anisoplanatism as a function of pupil distortion is derived, an example of an off-axis parabola is given, and a convenient method for controlling pupil-aberration-generated anisoplanatism is proposed.

  7. A synthesis theory for self-oscillating adaptive systems /SOAS/

    NASA Technical Reports Server (NTRS)

    Horowitz, I.; Smay, J.; Shapiro, A.

    1974-01-01

    A quantitative synthesis theory is presented for the Self-Oscillating Adaptive System (SOAS), whose nonlinear element has a static, odd character with hard saturation. The synthesis theory is based upon the quasilinear properties of the SOAS to forced inputs, which permits the extension of quantitative linear feedback theory to the SOAS. A reasonable definition of optimum design is shown to be the minimization of the limit cycle frequency. The great advantages of the SOAS is its zero sensitivity to pure gain changes. However, quasilinearity and control of the limit cycle amplitude at the system output, impose additional constraints which partially or completely cancel this advantage, depending on the numerical values of the design parameters. By means of narrow-band filtering, an additional factor is introduced which permits trade-off between filter complexity and limit cycle frequency minimization.

  8. Optimal Control Modification for Robust Adaptation of Singularly Perturbed Systems with Slow Actuators

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.; Ishihara, Abraham; Stepanyan, Vahram; Boskovic, Jovan

    2009-01-01

    Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. The model matching conditions in the transformed time coordinate results in increase in the feedback gain and modification of the adaptive law.

  9. Adaptive neuro-fuzzy estimation of optimal lens system parameters

    NASA Astrophysics Data System (ADS)

    Petković, Dalibor; Pavlović, Nenad T.; Shamshirband, Shahaboddin; Mat Kiah, Miss Laiha; Badrul Anuar, Nor; Idna Idris, Mohd Yamani

    2014-04-01

    Due to the popularization of digital technology, the demand for high-quality digital products has become critical. The quantitative assessment of image quality is an important consideration in any type of imaging system. Therefore, developing a design that combines the requirements of good image quality is desirable. Lens system design represents a crucial factor for good image quality. Optimization procedure is the main part of the lens system design methodology. Lens system optimization is a complex non-linear optimization task, often with intricate physical constraints, for which there is no analytical solutions. Therefore lens system design provides ideal problems for intelligent optimization algorithms. There are many tools which can be used to measure optical performance. One very useful tool is the spot diagram. The spot diagram gives an indication of the image of a point object. In this paper, one optimization criterion for lens system, the spot size radius, is considered. This paper presents new lens optimization methods based on adaptive neuro-fuzzy inference strategy (ANFIS). This intelligent estimator is implemented using Matlab/Simulink and the performances are investigated.

  10. Image-quality metrics for characterizing adaptive optics system performance.

    PubMed

    Brigantic, R T; Roggemann, M C; Bauer, K W; Welsh, B M

    1997-09-10

    Adaptive optics system (AOS) performance is a function of the system design, seeing conditions, and light level of the wave-front beacon. It is desirable to optimize the controllable parameters in an AOS to maximize some measure of performance. For this optimization to be useful, it is necessary that a set of image-quality metrics be developed that vary monotonically with the AOS performance under a wide variety of imaging environments. Accordingly, as conditions change, one can be confident that the computed metrics dictate appropriate system settings that will optimize performance. Three such candidate metrics are presented. The first is the Strehl ratio; the second is a novel metric that modifies the Strehl ratio by integration of the modulus of the average system optical transfer function to a noise-effective cutoff frequency at which some specified image spectrum signal-to-noise ratio level is attained; and the third is simply the cutoff frequency just mentioned. It is shown that all three metrics are correlated with the rms error (RMSE) between the measured image and the associated diffraction-limited image. Of these, the Strehl ratio and the modified Strehl ratio exhibit consistently high correlations with the RMSE across a broad range of conditions and system settings. Furthermore, under conditions that yield a constant average system optical transfer function, the modified Strehl ratio can still be used to delineate image quality, whereas the Strehl ratio cannot.

  11. On Cognition, Structured Sequence Processing, and Adaptive Dynamical Systems

    NASA Astrophysics Data System (ADS)

    Petersson, Karl Magnus

    2008-11-01

    Cognitive neuroscience approaches the brain as a cognitive system: a system that functionally is conceptualized in terms of information processing. We outline some aspects of this concept and consider a physical system to be an information processing device when a subclass of its physical states can be viewed as representational/cognitive and transitions between these can be conceptualized as a process operating on these states by implementing operations on the corresponding representational structures. We identify a generic and fundamental problem in cognition: sequentially organized structured processing. Structured sequence processing provides the brain, in an essential sense, with its processing logic. In an approach addressing this problem, we illustrate how to integrate levels of analysis within a framework of adaptive dynamical systems. We note that the dynamical system framework lends itself to a description of asynchronous event-driven devices, which is likely to be important in cognition because the brain appears to be an asynchronous processing system. We use the human language faculty and natural language processing as a concrete example through out.

  12. Regional Water System Vulnerabilities and Strengths for Unavoidable Climate Adaptation

    NASA Astrophysics Data System (ADS)

    Gleick, P. H.; Palaniappan, M.; Christian-Smith, J.; Cooley, H.

    2011-12-01

    A wide range of options are available to help water systems prepare and adapt for unavoidable climate impacts, but these options vary depending on region, climatic conditions, economic status, and technical infrastructure in place. Drawing on case studies from the United States, India, and elsewhere, and from both urban and agricultural water systems, risks to water supply and quality are evaluated and summarized and categories of responses to help improve the effectiveness of adaptation policies are reviewed. Among the issues to be discussed are characteristics unique to developing country cities, such as the predominance of informal actors in the water sector. The formal, or government sector, which often exclusively manages water access and distribution in developed country cities, is only one among many players in the water sector in developing country cities. Informal access to water includes direct access by individuals through private groundwater systems, private water markets using vendors or sales of bottled water, and rainwater harvesting systems on individual homes. In this environment, with already existing pressures on water availability and use, the impacts of climate change on water will be strongly felt. This complicates planning for water supply and demand and risks increasing already prevalent water insecurity, especially for urban poor. In wealthier countries, any planning for water-related climate impacts tends to take the form of "business as usual" responses, such as efforts to expand supply with new infrastructure, manage demand through conservation programs, or simply put off addressing the problem to the next generation of managers and users. These approaches can be effective, but also risk missing unusual, non-linear, or threshold impacts. Examples of more informed and innovative efforts to substantively address climate change risks will be presented.

  13. Personality Characteristic Adaptations: Multiracial Adolescents' Patterns of Racial Self-Identification Change

    ERIC Educational Resources Information Center

    Terry, Rodney L.; Winston, Cynthia E.

    2010-01-01

    For multiracial adolescents, forming a sense of self and identity can be complicated, even at the level of classifying themselves in terms of racial group membership. Using a Race Self Complexity (Winston et al., 2004) theoretical framework, this study used an open-ended question to examine the racial self-identification fluidity of 66 adolescents…

  14. Cross-Layer Self-Adaptive/Self-Aware System Software for Exascale Systems

    SciTech Connect

    Gioiosa, Roberto; Kestor, Gokcen; Kerbyson, Darren J.; Hoisie, Adolfy

    2014-10-22

    The extreme level of parallelism coupled with the limited available power budget expected in the exascale era brings unprecedented challenges that demand optimization of performance, power and resiliency in unison. Scalability on such systems is of paramount importance, while power and reliability issues may change the execution environment in which a parallel application runs. To solve these challenges exascale systems will require an introspective system software that combines system and application observations across all system stack layers with online feedback and adaptation mechanisms. In this paper we propose the design of a novel self-aware, self-adaptive system software in which a kernel-level Monitor, which continuously inspects the evolution of the target system through observation of Sensors, is combined with a user-level Controller, which reacts to changes in the execution environment, explores opportunities to increase performance, save power and adapts applications to new execution scenarios. We show that the monitoring system accurately monitors the evolution of parallel applications with a runtime overhead below 1-2%. As a test case, we design and implement a user-runtime system that aims at optimizing application’s performance and system power consumption on complex hierarchical architectures. Our results show that our adaptive system reaches 98% of performance efficiency of manually-tuned applications.

  15. The FIGS (focused identification of germplasm strategy) approach identifies traits related to drought adaptation in Vicia faba genetic resources.

    PubMed

    Khazaei, Hamid; Street, Kenneth; Bari, Abdallah; Mackay, Michael; Stoddard, Frederick L

    2013-01-01

    Efficient methods to explore plant agro-biodiversity for climate change adaptive traits are urgently required. The focused identification of germplasm strategy (FIGS) is one such approach. FIGS works on the premise that germplasm is likely to reflect the selection pressures of the environment in which it developed. Environmental parameters describing plant germplasm collection sites are used as selection criteria to improve the probability of uncovering useful variation. This study was designed to test the effectiveness of FIGS to search a large faba bean (Vicia faba L.) collection for traits related to drought adaptation. Two sets of faba bean accessions were created, one from moisture-limited environments, and the other from wetter sites. The two sets were grown under well watered conditions and leaf morpho-physiological traits related to plant water use were measured. Machine-learning algorithms split the accessions into two groups based on the evaluation data and the groups created by this process were compared to the original climate-based FIGS sets. The sets defined by trait data were in almost perfect agreement to the FIGS sets, demonstrating that ecotypic differentiation driven by moisture availability has occurred within the faba bean genepool. Leaflet and canopy temperature as well as relative water content contributed more than other traits to the discrimination between sets, indicating that their utility as drought-tolerance selection criteria for faba bean germplasm. This study supports the assertion that FIGS could be an effective tool to enhance the discovery of new genes for abiotic stress adaptation.

  16. Development of an expert system for amino acid sequence identification.

    PubMed

    Hu, L; Saulinskas, E F; Johnson, P; Harrington, P B

    1996-08-01

    An expert system for amino acid sequence identification has been developed. The algorithm uses heuristic rules developed by human experts in protein sequencing. The system is applied to the chromatographic data of phenylthiohydantoin-amino acids acquired from an automated sequencer. The peak intensities in the current cycle are compared with those in the previous cycle, while the calibration and succeeding cycles are used as ancillary identification criteria when necessary. The retention time for each chromatographic peak in each cycle is corrected by the corresponding peak in the calibration cycle at the same run. The main improvement of our system compared with the onboard software used by the Applied Biosystems 477A Protein/Peptide Sequencer is that each peak in each cycle is assigned an identification name according to the corrected retention time to be used for the comparison with different cycles. The system was developed from analyses of ribonuclease A and evaluated by runs of four other protein samples that were not used in rule development. This paper demonstrates that rules developed by human experts can be automatically applied to sequence assignment. The expert system performed more accurately than the onboard software of the protein sequencer, in that the misidentification rates for the expert system were around 7%, whereas those for the onboard software were between 13 and 21%.

  17. Does the Sympathetic Nervous System Adapt to Chronic Altitude Exposure?

    PubMed

    Sander, Mikael

    2016-01-01

    During continued exposure to hypobaric hypoxia in acclimatizing lowlanders increasing norepinephrine levels indirectly indicate sympathoexcitation, and in a few subjects serial measurements have suggested some adaptation over time. A few studies have provided direct microneurographic evidence for markedly increased muscle sympathetic nervous activity (MSNA) after 1-50 days of exposure of lowlanders to altitudes of 4100-5260 m above sea level. Only one study has provided two MSNA-measurements over time (10 and 50 days) in altitude (4100 m above sea level) and continued robust sympathoexcitation without adaptation was found in acclimatizing lowlanders. In this study, norepinephrine levels during rest and exercise also remained highly elevated over time. In comparison, acute exposure to hypoxic breathing (FiO2 0.126) at sea level caused no change in sympathetic nervous activity, although the same oxygen saturation in arterial blood (around 90 %) was present during acute (FiO2 0.126) and chronic hypoxic exposure (4100 m above sea level). These findings strongly suggest that the chemoreflex-mechanisms underlying acute hypoxia-induced increases in MSNA are sensitized over time. Collectively, the MSNA data suggests that sensitization of the sympathoexcitatory chemoreflex is evident but not complete within the first 24 h, but is complete after 10 days of altitude exposure. After return from high altitude to sea level the MSNA remains significantly elevated for at least 5 days but completely normalized after 3 months. The few MSNA measurements in high altitude natives have documented high sympathetic activity in all subjects studied. Because serial measurements of MSNA in high altitude natives during sea level exposure are lacking, it is unclear whether the sympathetic nervous system have somehow adapted to lifelong altitude exposure. PMID:27343109

  18. Adaptation Patterns as a Conceptual Tool for Designing the Adaptive Operation of CSCL Systems

    ERIC Educational Resources Information Center

    Karakostas, Anastasios; Demetriadis, Stavros

    2011-01-01

    While adaptive collaboration support has become the focus of increasingly intense research efforts in the CSCL domain, scarce, however, remain the research-based evidence on pedagogically useful ideas on what and how to adapt during the collaborative learning activity. Based principally on two studies, this work presents a compilation of…

  19. Systematic identification of genes and transduction pathways involved in radio-adaptive response

    SciTech Connect

    Wu, Honglu

    2015-05-22

    Low doses of radiation have been shown to protect against the biological effects of later exposure to toxic levels of radiation. In this study, we propose to identify the molecular mechanisms of this adaptive response by systematically identifying the genes that play a role in radio-protection. In the original proposal, a human cell line that is well-documented to exhibit the radio-adaptive effect was to be used. In this revised study plan, we will use a mouse model, C57BL/6, which has also been well investigated for radio-adaptation. The goal of the proposed study is to enhance our understanding of cellular responses to low doses of radiation exposure at the molecular level.

  20. Closed Loop System Identification with Genetic Algorithms

    NASA Technical Reports Server (NTRS)

    Whorton, Mark S.

    2004-01-01

    High performance control design for a flexible space structure is challenging since high fidelity plant models are di.cult to obtain a priori. Uncertainty in the control design models typically require a very robust, low performance control design which must be tuned on-orbit to achieve the required performance. Closed loop system identi.cation is often required to obtain a multivariable open loop plant model based on closed-loop response data. In order to provide an accurate initial plant model to guarantee convergence for standard local optimization methods, this paper presents a global parameter optimization method using genetic algorithms. A minimal representation of the state space dynamics is employed to mitigate the non-uniqueness and over-parameterization of general state space realizations. This control-relevant system identi.cation procedure stresses the joint nature of the system identi.cation and control design problem by seeking to obtain a model that minimizes the di.erence between the predicted and actual closed-loop performance.

  1. An Adaptive Scaffolding E-Learning System for Middle School Students' Physics Learning

    ERIC Educational Resources Information Center

    Chen, Ching-Huei

    2014-01-01

    This study presents a framework that utilizes cognitive and motivational aspects of learning to design an adaptive scaffolding e-learning system. It addresses scaffolding processes and conditions for designing adaptive scaffolds. The features and effectiveness of this adaptive scaffolding e-learning system are discussed and evaluated. An…

  2. Adaptability of solar energy conversion systems on ships

    NASA Astrophysics Data System (ADS)

    Visa, I.; Cotorcea, A.; Neagoe, M.; Moldovan, M.

    2016-08-01

    International trade of goods largely uses maritime/transoceanic ships driven by engines using fossil fuels. This two centuries tradition is technologically mature but significantly adds to the CO2 emissions; therefore, recent trends focus on on-board implementation of systems converting the solar energy into power (photovoltaic systems) or heat (solar-thermal systems). These systems are carbon-emissions free but are still under research and plenty of effort is devoted to fast reach maturity and feasibility. Unlike the systems implemented in a specific continental location, the design of solar energy conversion systems installed on shipboard has to face the problem generated by the system base motion along with the ship travelling on routes at different latitudes: the navigation direction and sense and roll-pitch combined motion with reduced amplitude, but with relatively high frequency. These raise highly interesting challenges in the design and development of mechanical systems that support the maximal output in terms of electricity or heat. The paper addresses the modelling of the relative position of a solar energy conversion surface installed on a ship according to the current position of the sun; the model is based on the navigation trajectory/route, ship motion generated by waves and the relative sun-earth motion. The model describes the incidence angle of the sunray on the conversion surface through five characteristic angles: three used to define the ship orientation and two for the solar angles; based on, their influence on the efficiency in solar energy collection is analyzed by numerical simulations and appropriate recommendations are formulated for increasing the solar energy conversion systems adaptability on ships.

  3. Multi-agent system for target-adaptive radar tracking

    NASA Astrophysics Data System (ADS)

    O'Connor, Alan C.

    2012-06-01

    Sensor systems such as distributed sensor networks and radar systems are potentially agile - they have parameters that can be adjusted in real-time to improve the quality of data obtained for state-estimation and decision-making. The integration of such sensors with cyber systems involving many users or agents permits greater flexibility in choosing measurement actions. This paper considers the problem of selecting radar waveforms to minimize uncertainty about the state of a tracked target. Past work gave a tractable method for optimizing the choice of measurements when an accurate dynamical model is available. However, prior knowledge about a system is often not precise, for example, if the target under observation is an adversary. A multiple agent system is proposed to solve the problem in the case of uncertain target dynamics. Each agent has a different target model and the agents compete to explain past data and select the parameters of future measurements. Collaboration or competition between these agents determines which obtains access to the limited physical sensing resources. This interaction produces a self-aware sensor that adapts to changing information requirements.

  4. Fast and Adaptive Lossless Onboard Hyperspectral Data Compression System

    NASA Technical Reports Server (NTRS)

    Aranki, Nazeeh I.; Keymeulen, Didier; Kimesh, Matthew A.

    2012-01-01

    Modern hyperspectral imaging systems are able to acquire far more data than can be downlinked from a spacecraft. Onboard data compression helps to alleviate this problem, but requires a system capable of power efficiency and high throughput. Software solutions have limited throughput performance and are power-hungry. Dedicated hardware solutions can provide both high throughput and power efficiency, while taking the load off of the main processor. Thus a hardware compression system was developed. The implementation uses a field-programmable gate array (FPGA). The implementation is based on the fast lossless (FL) compression algorithm reported in Fast Lossless Compression of Multispectral-Image Data (NPO-42517), NASA Tech Briefs, Vol. 30, No. 8 (August 2006), page 26, which achieves excellent compression performance and has low complexity. This algorithm performs predictive compression using an adaptive filtering method, and uses adaptive Golomb coding. The implementation also packetizes the coded data. The FL algorithm is well suited for implementation in hardware. In the FPGA implementation, one sample is compressed every clock cycle, which makes for a fast and practical realtime solution for space applications. Benefits of this implementation are: 1) The underlying algorithm achieves a combination of low complexity and compression effectiveness that exceeds that of techniques currently in use. 2) The algorithm requires no training data or other specific information about the nature of the spectral bands for a fixed instrument dynamic range. 3) Hardware acceleration provides a throughput improvement of 10 to 100 times vs. the software implementation. A prototype of the compressor is available in software, but it runs at a speed that does not meet spacecraft requirements. The hardware implementation targets the Xilinx Virtex IV FPGAs, and makes the use of this compressor practical for Earth satellites as well as beyond-Earth missions with hyperspectral instruments.

  5. Configurable multiplier modules for an adaptive computing system

    NASA Astrophysics Data System (ADS)

    Pfänder, O. A.; Pfleiderer, H.-J.; Lachowicz, S. W.

    2006-09-01

    The importance of reconfigurable hardware is increasing steadily. For example, the primary approach of using adaptive systems based on programmable gate arrays and configurable routing resources has gone mainstream and high-performance programmable logic devices are rivaling traditional application-specific hardwired integrated circuits. Also, the idea of moving from the 2-D domain into a 3-D design which stacks several active layers above each other is gaining momentum in research and industry, to cope with the demand for smaller devices with a higher scale of integration. However, optimized arithmetic blocks in course-grain reconfigurable arrays as well as field-programmable architectures still play an important role. In countless digital systems and signal processing applications, the multiplication is one of the critical challenges, where in many cases a trade-off between area usage and data throughput has to be made. But the a priori choice of word-length and number representation can also be replaced by a dynamic choice at run-time, in order to improve flexibility, area efficiency and the level of parallelism in computation. In this contribution, we look at an adaptive computing system called 3-D-SoftChip to point out what parameters are crucial to implement flexible multiplier blocks into optimized elements for accelerated processing. The 3-D-SoftChip architecture uses a novel approach to 3-dimensional integration based on flip-chip bonding with indium bumps. The modular construction, the introduction of interfaces to realize the exchange of intermediate data, and the reconfigurable sign handling approach will be explained, as well as a beneficial way to handle and distribute the numerous required control signals.

  6. Design of infrasound-detection system via adaptive LMSTDE algorithm

    NASA Technical Reports Server (NTRS)

    Khalaf, C. S.; Stoughton, J. W.

    1984-01-01

    A proposed solution to an aviation safety problem is based on passive detection of turbulent weather phenomena through their infrasonic emission. This thesis describes a system design that is adequate for detection and bearing evaluation of infrasounds. An array of four sensors, with the appropriate hardware, is used for the detection part. Bearing evaluation is based on estimates of time delays between sensor outputs. The generalized cross correlation (GCC), as the conventional time-delay estimation (TDE) method, is first reviewed. An adaptive TDE approach, using the least mean square (LMS) algorithm, is then discussed. A comparison between the two techniques is made and the advantages of the adaptive approach are listed. The behavior of the GCC, as a Roth processor, is examined for the anticipated signals. It is shown that the Roth processor has the desired effect of sharpening the peak of the correlation function. It is also shown that the LMSTDE technique is an equivalent implementation of the Roth processor in the time domain. A LMSTDE lead-lag model, with a variable stability coefficient and a convergence criterion, is designed.

  7. An Adaptable Power System with Software Control Algorithm

    NASA Technical Reports Server (NTRS)

    Castell, Karen; Bay, Mike; Hernandez-Pellerano, Amri; Ha, Kong

    1998-01-01

    A low cost, flexible and modular spacecraft power system design was developed in response to a call for an architecture that could accommodate multiple missions in the small to medium load range. Three upcoming satellites will use this design, with one launch date in 1999 and two in the year 2000. The design consists of modular hardware that can be scaled up or down, without additional cost, to suit missions in the 200 to 600 Watt orbital average load range. The design will be applied to satellite orbits that are circular, polar elliptical and a libration point orbit. Mission unique adaptations are accomplished in software and firmware. In designing this advanced, adaptable power system, the major goals were reduction in weight volume and cost. This power system design represents reductions in weight of 78 percent, volume of 86 percent and cost of 65 percent from previous comparable systems. The efforts to miniaturize the electronics without sacrificing performance has created streamlined power electronics with control functions residing in the system microprocessor. The power system design can handle any battery size up to 50 Amp-hour and any battery technology. The three current implementations will use both nickel cadmium and nickel hydrogen batteries ranging in size from 21 to 50 Amp-hours. Multiple batteries can be used by adding another battery module. Any solar cell technology can be used and various array layouts can be incorporated with no change in Power System Electronics (PSE) hardware. Other features of the design are the standardized interfaces between cards and subsystems and immunity to radiation effects up to 30 krad Total Ionizing Dose (TID) and 35 Mev/cm(exp 2)-kg for Single Event Effects (SEE). The control algorithm for the power system resides in a radiation-hardened microprocessor. A table driven software design allows for flexibility in mission specific requirements. By storing critical power system constants in memory, modifying the system

  8. Material Outgassing, Identification and Deposition, MOLIDEP System

    NASA Technical Reports Server (NTRS)

    Scialdone, John J.; Montoya, Alex F.

    2002-01-01

    The outgassing tests are performed employing a modified vacuum operated Cahn analytical microbalance, identified as the MOLIDEP system. The test measures under high vacuum, the time varying Molecular mass loss of a material sample held at a chosen temperature; it Identifies the outgassing molecular components using an inline SRS 300 amu Residual Gas Analyzer (RGA) and employs a temperature controlled 10 MHz Quartz Crystal Microbalance (QCM) to measure the condensable DEPosits. Both the QCM and the RGA intercept within the conductive passage the outgassing products being evacuated by a turbomolecular pump. The continuous measurements of the mass loss, the rate of loss, the sample temperature, the rate of temperature change, the QCM temperature and the QCM recorded condensable deposits or rate of deposits are saved to an Excel spreadsheet. A separate computer controls the RGA.

  9. Prefire identification for pulse power systems

    DOEpatents

    Longmire, Jerry L.; Thuot, Michael E.; Warren, David S.

    1985-01-01

    Prefires in a high-power, high-frequency, multi-stage pulse generator are detected by a system having an EMI shielded pulse timing transmitter associated with and tailored to each stage of the pulse generator. Each pulse timing transmitter upon detection of a pulse triggers a laser diode to send an optical signal through a high frequency fiber optic cable to a pulse timing receiver which converts the optical signal to an electrical pulse. The electrical pulses from all pulse timing receivers are fed through an OR circuit to start a time interval measuring device and each electrical pulse is used to stop an individual channel in the measuring device thereby recording the firing sequence of the multi-stage pulse generator.

  10. Prefire identification for pulse-power systems

    DOEpatents

    Longmire, J.L.; Thuot, M.E.; Warren, D.S.

    1982-08-23

    Prefires in a high-power, high-frequency, multi-stage pulse generator are detected by a system having an EMI shielded pulse timing transmitter associated with and tailored to each stage of the pulse generator. Each pulse timing transmitter upon detection of a pulse triggers a laser diode to send an optical signal through a high frequency fiber optic cable to a pulse timing receiver which converts the optical signal to an electrical pulse. The electrical pulses from all pulse timing receivers are fed through an OR circuit to start a time interval measuring device and each electrical pulse is used to stop an individual channel in the measuring device thereby recording the firing sequence of the multi-stage pulse generator.

  11. Torsional system parameter identification of internal combustion engines under normal operation

    NASA Astrophysics Data System (ADS)

    Östman, Fredrik; Toivonen, Hannu T.

    2011-05-01

    For internal combustion engines, lumped-mass models of the crankshaft system are frequently used for torque estimation in control and diagnostic applications, such as cylinder balancing and misfire detection. Due to inherent model uncertainties and changing system dynamics it may be necessary to adapt the model parameters from time to time in order to preserve the required model accuracy. In this paper a frequency-domain method for on-line identification of the parameters describing the torsional dynamics of internal combustion engines is presented. In the proposed method, the engine is excited by adjusting the cylinder-wise injected fuel amounts, and the measured responses in torsional vibration frequency components are used for parameter estimation. As the fuel-injection adjustments can be determined in such a way that the net indicated torque is unaffected, the identification can be performed on-line without disturbing normal engine operation. The procedure can be applied to estimate the torsional stiffness and damping parameters of the flexible coupling connecting the engine and the load. In addition, the gains which describe how the cylinder-wise fuel injections affect the amplitudes of relevant torsional vibratory frequency components are obtained. The parameter identification method is successfully evaluated in full-scale engine tests on a 6.6 MW six-cylinder medium-speed common-rail diesel engine.

  12. Neural Networks and other Techniques for Fault Identification and Isolation of Aircraft Systems

    NASA Technical Reports Server (NTRS)

    Innocenti, M.; Napolitano, M.

    2003-01-01

    Fault identification, isolation, and accomodation have become critical issues in the overall performance of advanced aircraft systems. Neural Networks have shown to be a very attractive alternative to classic adaptation methods for identification and control of non-linear dynamic systems. The purpose of this paper is to show the improvements in neural network applications achievable through the use of learning algorithms more efficient than the classic Back-Propagation, and through the implementation of the neural schemes in parallel hardware. The results of the analysis of a scheme for Sensor Failure, Detection, Identification and Accommodation (SFDIA) using experimental flight data of a research aircraft model are presented. Conventional approaches to the problem are based on observers and Kalman Filters while more recent methods are based on neural approximators. The work described in this paper is based on the use of neural networks (NNs) as on-line learning non-linear approximators. The performances of two different neural architectures were compared. The first architecture is based on a Multi Layer Perceptron (MLP) NN trained with the Extended Back Propagation algorithm (EBPA). The second architecture is based on a Radial Basis Function (RBF) NN trained with the Extended-MRAN (EMRAN) algorithms. In addition, alternative methods for communications links fault detection and accomodation are presented, relative to multiple unmanned aircraft applications.

  13. Identification of a novel cell culture adaptation site on the capsid of foot-and-mouth disease virus.

    PubMed

    Chamberlain, Kyle; Fowler, Veronica L; Barnett, Paul V; Gold, Sarah; Wadsworth, Jemma; Knowles, Nick J; Jackson, Terry

    2015-09-01

    Vaccination remains the most effective tool for control of foot-and-mouth disease both in endemic countries and as an emergency preparedness for new outbreaks. Foot-and-mouth disease vaccines are chemically inactivated virus preparations and the production of new vaccines is critically dependent upon cell culture adaptation of field viruses, which can prove problematic. A major driver of cell culture adaptation is receptor availability. Field isolates of foot-and-mouth disease virus (FMDV) use RGD-dependent integrins as receptors, whereas cell culture adaptation often selects for variants with altered receptor preferences. Previously, two independent sites on the capsid have been identified where mutations are associated with improved cell culture growth. One is a shallow depression formed by the three major structural proteins (VP1-VP3) where mutations create a heparan sulphate (HS)-binding site (the canonical HS-binding site). The other involves residues of VP1 and is located at the fivefold symmetry axis. For some viruses, changes at this site result in HS binding; for others, the receptors are unknown. Here, we report the identification of a novel site on VP2 where mutations resulted in an expanded cell tropism of a vaccine variant of A/IRN/87 (called A - ). Furthermore, we show that introducing the same mutations into a different type A field virus (A/TUR/2/2006) resulted in the same expanded cell culture tropism as the A/IRN/87 A -  vaccine variant. These observations add to the evidence for multiple cell attachment mechanisms for FMDV and may be useful for vaccine manufacture when cell culture adaptation proves difficult.

  14. System Identification in Presence of Outliers.

    PubMed

    Yu, Chao; Wang, Qing-Guo; Zhang, Dan; Wang, Lei; Huang, Jiangshuai

    2016-05-01

    The outlier detection problem for dynamic systems is formulated as a matrix decomposition problem with low rank and sparse matrices, and further recast as a semidefinite programming problem. A fast algorithm is presented to solve the resulting problem while keeping the solution matrix structure and it can greatly reduce the computational cost over the standard interior-point method. The computational burden is further reduced by proper construction of subsets of the raw data without violating low-rank property of the involved matrix. The proposed method can make exact detection of outliers in case of no or little noise in output observations. In case of significant noise, a novel approach based on under-sampling with averaging is developed to denoise while retaining the saliency of outliers, and so-filtered data enables successful outlier detection with the proposed method while the existing filtering methods fail. Use of recovered "clean" data from the proposed method can give much better parameter estimation compared with that based on the raw data.

  15. Seizure prediction using adaptive neuro-fuzzy inference system.

    PubMed

    Rabbi, Ahmed F; Azinfar, Leila; Fazel-Rezai, Reza

    2013-01-01

    In this study, we present a neuro-fuzzy approach of seizure prediction from invasive Electroencephalogram (EEG) by applying adaptive neuro-fuzzy inference system (ANFIS). Three nonlinear seizure predictive features were extracted from a patient's data obtained from the European Epilepsy Database, one of the most comprehensive EEG database for epilepsy research. A total of 36 hours of recordings including 7 seizures was used for analysis. The nonlinear features used in this study were similarity index, phase synchronization, and nonlinear interdependence. We designed an ANFIS classifier constructed based on these features as input. Fuzzy if-then rules were generated by the ANFIS classifier using the complex relationship of feature space provided during training. The membership function optimization was conducted based on a hybrid learning algorithm. The proposed method achieved highest sensitivity of 80% with false prediction rate as low as 0.46 per hour. PMID:24110134

  16. Probing other solar systems with current and future adaptive optics

    SciTech Connect

    Macintosh, B; Marois, C; Phillion, D; Poyneer, L; Graham, J; Zuckerman, B; Gavel, D; Veran, J; Wilhelmsen-Evans, J; Mellis, C

    2008-09-08

    Over the past decade, the study of extrasolar planets through indirect techniques--primarily Doppler measurements--has revolutionized our understanding of other solar systems. The next major step in this field will be the direct detection and characterization, via imaging and spectroscopy, of the planets themselves. To achieve this, we must separate the light from the faint planet from the extensive glare of its parent star. We pursued this goal using the current generation of adaptive optics (AO) systems on large ground-based telescopes, using infrared imaging to search for the thermal emission from young planets and developing image processing techniques to distinguish planets from telescope-induced artifacts. Our new Angular Differential Imaging (ADI) technique, which uses the sidereal rotation of the Earth and telescope, is now standard for ground-based high-contrast imaging. Although no young planets were found in our surveys, we placed the strongest limits yet on giant planets in wide orbits (>30 AU) around young stars and characterized planetary companion candidates. The imaging of planetary companions on solar-system-like scales (5-30 AU) will require a new generation of advanced AO systems that are an order of magnitude more powerful than the LLNL-built Keck AO system. We worked to develop and test the key technologies needed for these systems, including a spatially-filtered wavefront sensor, efficient and accurate wavefront reconstruction algorithms, and precision AO wavefront control at the sub-nm level. LLNL has now been selected by the Gemini Observatory to lead the construction of the Gemini Planet Imager, a $24M instrument that will be the most advanced AO system in the world.

  17. System Identification and POD Method Applied to Unsteady Aerodynamics

    NASA Technical Reports Server (NTRS)

    Tang, Deman; Kholodar, Denis; Juang, Jer-Nan; Dowell, Earl H.

    2001-01-01

    The representation of unsteady aerodynamic flow fields in terms of global aerodynamic modes has proven to be a useful method for reducing the size of the aerodynamic model over those representations that use local variables at discrete grid points in the flow field. Eigenmodes and Proper Orthogonal Decomposition (POD) modes have been used for this purpose with good effect. This suggests that system identification models may also be used to represent the aerodynamic flow field. Implicit in the use of a systems identification technique is the notion that a relative small state space model can be useful in describing a dynamical system. The POD model is first used to show that indeed a reduced order model can be obtained from a much larger numerical aerodynamical model (the vortex lattice method is used for illustrative purposes) and the results from the POD and the system identification methods are then compared. For the example considered, the two methods are shown to give comparable results in terms of accuracy and reduced model size. The advantages and limitations of each approach are briefly discussed. Both appear promising and complementary in their characteristics.

  18. A fuzzy logic system for Raman spectrum identification

    NASA Astrophysics Data System (ADS)

    Castanys, M.; Soneira, M. J.; Perez-Pueyo, R.; Ruiz-Moreno, S.

    2005-06-01

    Raman Spectroscopy is a fast, rugged analytical technique based on the Raman Effect. When monochromatic light encounters matter, most of the scattered light has the same wavelength as the incident light. However, a small fraction of the scattered light is shifted in a different wavelength by the molecular vibrations and rotations in the sample. The representation of this shifted light is called Raman spectrum, and contains many sharp bands characteristics of the sample, allowing its identification without ambiguity. In this communication, a fuzzy logic system to recognize Raman spectra of artistic pigments is presented. The identification is based on the comparison between an unknown spectrum, and pattern spectra. Frequently the comparison is made by the spectrospist by visual inspection, but this is slow and imprecise. In order to mitigate this problematic, a system based on the fuzzy logic technique to identify Raman spectra is presented. The methodology consists on implementing the comparison with the Correlation. However, a Raman spectrum is inevitably affected by noise which introduces ambiguity into the correlation values. Fuzzy Logic provides a simple way to draw conclusions from imprecise data. The fuzzy identification system is based on the following statement: when the correlation between the unidentified and the pattern is enough high, the analysed pigment is recognized as the pigment which corresponds to this pattern. The membership functions, which characterize the fuzzy sets at the input (Correlation) and output (Identified/ Not_Identified) of the system, and the inference mechanism suitable for the problem, are chosen.

  19. Optimal Control Modification Adaptive Law for Time-Scale Separated Systems

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.

    2010-01-01

    Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. A model matching conditions in the transformed time coordinate results in an increase in the actuator command that effectively compensate for the slow actuator dynamics. Simulations demonstrate effectiveness of the method.

  20. Time-frequency characterization of nonlinear normal modes and challenges in nonlinearity identification of dynamical systems

    NASA Astrophysics Data System (ADS)

    Pai, P. Frank

    2011-10-01

    Presented here is a new time-frequency signal processing methodology based on Hilbert-Huang transform (HHT) and a new conjugate-pair decomposition (CPD) method for characterization of nonlinear normal modes and parametric identification of nonlinear multiple-degree-of-freedom dynamical systems. Different from short-time Fourier transform and wavelet transform, HHT uses the apparent time scales revealed by the signal's local maxima and minima to sequentially sift components of different time scales. Because HHT does not use pre-determined basis functions and function orthogonality for component extraction, it provides more accurate time-varying amplitudes and frequencies of extracted components for accurate estimation of system characteristics and nonlinearities. CPD uses adaptive local harmonics and function orthogonality to extract and track time-localized nonlinearity-distorted harmonics without the end effect that destroys the accuracy of HHT at the two data ends. For parametric identification, the method only needs to process one steady-state response (a free undamped modal vibration or a steady-state response to a harmonic excitation) and uses amplitude-dependent dynamic characteristics derived from perturbation analysis to determine the type and order of nonlinearity and system parameters. A nonlinear two-degree-of-freedom system is used to illustrate the concepts and characterization of nonlinear normal modes, vibration localization, and nonlinear modal coupling. Numerical simulations show that the proposed method can provide accurate time-frequency characterization of nonlinear normal modes and parametric identification of nonlinear dynamical systems. Moreover, results show that nonlinear modal coupling makes it impossible to decompose a general nonlinear response of a highly nonlinear system into nonlinear normal modes even if nonlinear normal modes exist in the system.